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Applied AI Engineer

Applied AI Engineer

Location: Citi Field – Queens, New York

Summary

The New York Mets are seeking an Applied AI Engineer to build and ship production-grade AI capabilities that improve decision-making and streamline workflows across Baseball Operations. This role sits at the intersection of Baseball Systems (software engineering), Data Engineering, Baseball Analytics, Performance Technology, and modern generative AI. You will develop reliable AI-powered applications such as retrieval-augmented generation (RAG), secure tool/data integrations (MCP-style patterns), and agentic workflows that can support deep work and research, while ensuring strong standards for quality, security, privacy, and operational excellence.

This is a hands-on role for an engineer who can translate ambiguous baseball operations and player development needs into working software, iterate quickly with stakeholders, and harden solutions into durable systems used daily by analysts, coaches, scouts, and baseball operations staff.

Note: This role will require extensive in-person collaboration and innovation alongside stakeholders, analysts, and engineers. Applicants must be local to NYC (or willing to relocate) and be able to travel to Citi Field regularly. Travel to Spring Training and affiliates may also be required.

Essential Duties & Responsibilities

• Design, build and maintain AI-powered product experiences that provide intuitive access to baseball information and statistics and workflows across internal systems.

• Develop end-to-end RAG pipelines (ingest, chunking, embedding, retrieval, generation) with strong attention to answer quality, baseball relevancy, analytics accuracy, latency, and cost.

• Implement secure tool and data connectors for AI assistants and agents using standardized patterns (MCP-style), enabling safe interaction with internal APIs, data warehouses, and services.

• Build agentic workflows that can execute multi-step tasks (research, analysis, synthesis, report generation) with clear guardrails, auditability, and human-in-the-loop approvals.

• Partner closely with Product, Analytics, Performance Technology, Player Development, and Baseball operations stakeholders to frame problems, define success, and deliver measurable impact.

• Contribute to shared engineering standards and reusable components so AI capabilities scale across multiple products and teams.

• Ensure strong security and privacy practices (access control, data boundaries, logging and auditing, and safe handling of sensitive information).

• Participate in high-availability support expectations as needed during critical operational periods throughout the baseball season, and during feature releases.

Qualifications

• Bachelor’s degree in Computer Science or equivalent practical experience.

• 5+ years of professional software engineering experience, including building and operating production services.

• Demonstrated experience building LLM-powered applications in production (prompt/program design, structured outputs, tool calling, reliability patterns).

• Practical experience with retrieval systems (search, embeddings, vector databases, ranking, chunking/indexing) and applying them to real workflows.

• Strong experience with modern backend and data integration fundamentals: APIs, SQL, distributed systems, and cloud infrastructure (GCP/AWS/Azure)

• Proficiency in one or more production languages commonly used for AI applications and services (e.g. Python and/or Typescript)

• Approach work as highly collaborative and stakeholder-driven, with the ability to operate in ambiguity while iterating quickly.

• Strong written and verbal communication skills with the ability to explain tradeoffs to technical and non-technical audiences.

• Experience working in sports, health, finance, or other high-stakes analytics-heavy environments, preferred.

• Strong interest in baseball and comfort working within the culture of a professional sports organization, preferred

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets value the unique qualities individuals with various backgrounds and experiences can offer the organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

Salary Range: $180,000 – $200,000

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

The content in this posting was created and provided solely by the New York Mets.

Direct link to application (please see job details below):

Analyst – Baseball Strategy

Analyst – Baseball Strategy

Location: Pittsburgh

The Pirates Why

The Pittsburgh Pirates are a storied franchise in Major League Baseball who are reinventing themselves on every level. Boldly and relentlessly pursuing excellence by:

• purposefully developing a player and people-centered culture;
• deeply connecting with our fans, partners, and colleagues;
• passionately creating lifetime memories for generations of families and friends; and
• meaningfully impacting our communities and the game of baseball.

At the Pirates, we believe in the power of a diverse workforce and strive to create an inclusive culture centered in Passion, Innovation, Respect, Accountability, Teamwork, Empathy, and Service.

Job Summary

The Strategy team with the Pittsburgh Pirates exists to give the Major League coaching staff the information and tools they need to make elite in-game decisions. The group’s analysts translate information into clear, actionable plans that support both daily competition and long-term player growth.

The Baseball Strategy team will be considering applicants at both the Analyst and Senior Analyst level. In this role, you’ll work alongside Major League coaches and staff, helping turn information into on-field impact. Your work will include elements of game preparation, in-game strategy support, post-game review, skill development, and ongoing tool or process improvement.

Responsibilities:

1. Partner with Major League coaches to build strong working relationships, understand the decisions they face, and identify where analysis can create a competitive advantage.

2. Connect research to real baseball questions by turning observations from coaches, players, and data into testable ideas and pursuing the questions most likely to inform decisions or improve performance.

3. Support the daily competitive process by contributing to game preparation, in-game strategy support, post-game review, and player development while balancing immediate needs with longer-term projects.

4. Improve tools and processes by building and refining analytical resources that fit staff workflows and make useful information easier to access and apply.

5. Collaborate across baseball operations by working with analysts, researchers, coaches, and performance staff to combine different perspectives, surface disagreements constructively, and move shared work forward.

Qualifications

Required:

1. Authorized to work lawfully in the United States.
2. Demonstrated ability to synthesize complex information into actionable recommendations.
3. Proven ability to manage multiple projects and meet tight deadlines in a fast-paced setting.
4. Excellent communication and relationship-building skills.
5. Strong knowledge of modern baseball research and technologies.
6. Programming language proficiencies:
   • General purpose programming (Python or R)
   • Relational databases (SQL)
   • Familiarity with industry-relevant AI and automation tools to streamline daily workflows and tasks.

Desired:

1. Experience working with coaches, analysts, or player development staff in a high-performance environment.
2. Demonstrated baseball or other sports analytics research work product.
3. Practical and/or research experience with pitch design and modern pitching development techniques.
4. Proficiency with version control systems (e.g., Git) and collaborative development platforms like GitHub or GitLab.

Equal Opportunity Employer

The Pittsburgh Pirates are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.

To Apply
To apply, please follow this link.

The content in this posting was created and provided solely by the Pittsburgh Pirates.

The Tampa Bay Rays won the most games in the American League this year while running the AL’s second-lowest payroll. That’s a feat of team-building, first and foremost, but it also speaks to how well their players dodged leaks. On offense, they had the lowest strikeout and whiff rates in the majors; their pitchers had the league’s lowest walk rate and just 18 blown saves. You can’t make mistakes if you’re the Rays.

That’s a well-worn cliché, but here’s a novel spin on it: You can’t make mistakes if you’re the Yankees either. Presumptive AL Cy Young winner Cam Schlittler did some terrific work in his first career playoff road start, and no one’s going to remember it, because the other eight guys in gray pajamas played like the ball was covered in dish soap in Game 2.

The Yankees committed three errors in the bottom of the first inning, and another in the fifth. The Rays scored five runs across those two half-innings, and there’s your final score: Rays 5, Yankees 2. Read the rest of this entry »

Playoff losses can follow several different scripts, from the wire-to-wire blowouts that breed prolonged helplessness to the back-and-forth affairs that provide just enough hope before snatching it away at the end. But somewhere in the middle, there is the type of game that seems like a team can and should win, only for a few things to break the other way in such a fashion that its fans do not rage, do not cry, but instead climb aboard the doomsday hamster wheel of here we go again.

With their 4-3 loss to the Chicago White Sox in Game 2 of the American League Division Series, the Cleveland Guardians are now 2-7 in their last nine home playoff games. Those perilously loyal Cleveland fans, clad in red and blue jerseys bearing several different names — both on the front and the back — have seen their team repeatedly fall flat, dating back to that famous rain delay in 2016. But in this decade, they’ve also seen their team lose an ALDS Game 4 to the Yankees in 2022 that would have clinched the series, another loss to the Yankees in 2024 when Juan Soto simply decided he was too good of a hitter not to break their hearts, and two crushing Wild Card Series losses at home in 2025 to a division rival. In 2026, with no guarantee that they’ll be coming back for another game this year, the Guardians have added two more defeats at the hands of an AL Central foe, this time coming off a bye.

The White Sox won this game by eschewing the home run ball they relied on all summer and opting for Guards Ball. They had just three of the 10 hardest-hit balls of the game. Their opening pitcher did not get out of the first inning. But twice they scored from second on a single, went 3-for-8 with runners in scoring position (as opposed to Cleveland’s fatal 0-for-5), and rode a scorching hot reliever to probably their biggest victory since the 2005 championship march.

Ironically, this game began with a bit of Guards Ball from the home team that seemed a little too on the nose. Steven Kwan kicked things off with a roller through the right side that left the bat at 84.8 mph. José Ramírez then worked a walk, and Chase DeLauter followed with a productive out. That spelled the end of the night for Anthony Kay, who was replaced by Sean Newcomb. When Newcomb promptly missed the zone with his first two pitches to Jo Adell, the White Sox bench opted to put Adell on intentionally, loading the bases and setting up a double play. Newcomb was able to induce a grounder from Nathaniel Lowe next, but the type that bounces way up in the air rather than skimming along the dirt. It was also, apparently, the type of grounder that triggers a horrendous throwing error, giving Cleveland two easy runs.

The buildup to that calamitous moment wasn’t entirely Newcomb’s fault, as Kay was responsible for the lead runners and recorded one solitary out on just 17 pitches, both fewer than the four outs on 22 pitches he gave Chicago as a reliever in Game 1. What the White Sox do with Kay for the rest of the series may come down entirely to game situations; his Game 2 performance inspired negative confidence, and it seems he’s better suited for plug-and-play outings out of the bullpen, particularly with Davis Martin, Hagen Smith and/or Erick Fedde, and Sean Burke now lined up for the bulk roles should this series go all the way to Game 5.

For the first half of this game, Newcomb’s blunder looked like it would be the defining play. But the true inflection points came in the bottom of the fifth and the top of the sixth. Cleveland, clinging to a 2-1 lead, sent its best hitters to the plate in the home half of the fifth. Not only did that trio — Kwan, Ramírez, and DeLauter — go down in order, they did so without getting a ball out of the infield. Up to that point, the game was following a favorable script for the Guardians. They were gifted an early lead, had their starting pitcher, Gavin Williams, in the rocking chair, and were primed to put pressure on Chicago’s pitching staff. The exact pocket of the lineup that Cleveland manager Stephen Vogt would want at the plate for that situation wilted, and it felt like the White Sox were headed back to their dugout knowing their opponent had squandered their chance to properly put them away.

Within minutes, things began unraveling in Cleveland like the night Mike Love gave his Rock and Roll Hall of Fame speech. Miguel Vargas chased Williams by thwacking his 98th pitch of the night into left field for a sharp leadoff single. The Guardians then turned to lefty Erik Sabrowski, a very qualified fireman who came oh so close to extinguishing the flames. Sabrowski retired Munetaka Murakami and walked Randal Grichuk. No harm, no foul. But perhaps the biggest pitch of the night was one that did not get put in play or result in a strikeout. Rather, it was a wild pitch that pushed Vargas and Grichuk to third and second base, respectively. While Sabrowski did well to dig out of a 2-0 hole and pop Tommy Pham up for the second out, the next batter ambushed him.

Braden Montgomery’s first-pitch double was a wondrous display of hitting. It also would not have given Chicago the lead if not for Sabrowski’s wild pitch. One inning after Cleveland’s biggest (and some would say only) offensive threats failed to do anything, a defense-first rookie with an 89 wRC+ delivered the biggest blow of the night for Chicago. Fellow youngster Chase Meidroth then slapped an opposite-field single off Hunter Gaddis to make it 4-2 White Sox, and the here we go again feeling blew through Progressive Field like a vicious Lake Erie wind. Both Montgomery and Meidroth’s RBI knocks came on fastballs, pitch selections that Cleveland might like to have back. In the regular season, Montgomery had a .379 xwOBA against fastballs, and he was facing a pitcher in Sabrowski who hadn’t allowed a hit all year to righties on his slider. Meidroth — who whiffs on fastballs just 15.7% of the time, compared to 23.5% on breaking stuff and 29.3% on offspeed pitches — probably should have seen exclusively sliders and changeups from Gaddis.

The cruelty of this game for the Guardians is found in Williams’ stat line. Their flamethrowing Big Rig sat 99 mph on his fastball, generated 22 whiffs on 40 swings, and finished with 11 strikeouts. Apart from the three walks that drove his pitch count up — one of which helped the White Sox plate their first run in the fourth inning — Williams did everything that could have been asked of him, handing things over to a more than capable bullpen. It not only wasn’t enough, but it will be lost to history because of what Burke did.

Burke is a starting pitcher by trade, one who made 27 starts for the White Sox this year and led the team in innings. Starting pitchers, notorious creatures of habit that they are, typically don’t like following an opener. They especially don’t like entering a game mid-inning with a runner on base. But that’s exactly what Burke did in his spectacular Game 2 showing. When White Sox skipper Will Venable gave his early-inning interview on the television broadcast, he plainly stated that the plan was to have Kay and Newcomb get through DeLauter a second time. DeLauter singled in his second at-bat, immediately shooting Venable out of the dugout to go get Newcomb, as planned. But if you pumped Venable with truth serum, he’d likely tell you he was feeling a bit queasy about that plan now putting Burke in a dirty inning. Burke’s response to this adversity wasn’t as sexy as escaping a bases-loaded jam or coming on for a multi-inning save, but his subsequent strikeouts of both Adell and Lowe is the type of thing that should get a proper segment if this White Sox run turns documentary worthy. He goes to bed knowing he covered 5 1/3 innings while surrendering just one hit, and also that the Pope must be thrilled with him.

The Guardians, meanwhile, do not have papal fandom or many shreds of optimism on their side, both narratively and statistically. They lost two home games with their two best pitchers on the hill. Two of the three runs they’ve scored this series have come from a pitcher fielding his position and suddenly contracting Joel Zumaya Disease. They now have to win two games at Rate Field in Chicago, which will not only be completely bananas, but is a venue where they lost four of their six games this year. Maybe they can cling to the idea that Adell’s ultimately fruitless eighth-inning triple will unlock his swing, or that Grant Taylor has been so overworked that he can’t possibly continue pitching this well.

But once you start playing that mental game, it’s probably not going to happen for you, the same way it hasn’t happened for Cleveland in the postseason all decade.

When I’m trying to ground myself in the present, I like to repeat a mantra: No past, no future. I don’t want to dictate personal philosophy to you, but it works great for me. It’s a reminder to focus on the now, that experiencing what’s happening right this instant is more important than whatever mental baggage I’m carrying or whatever I’m worried might take place next week. I wholeheartedly suggest some variation of this phrase when you’re feeling overwhelmed by things that aren’t happening to you in the moment.

Having said that, let me be clear: You can’t ignore the past and future when you’re managing postseason pitching assignments, Walt Weiss. The Braves are five games into the playoffs, and they’ve been living the “no past, no future” life the entire time. Now, I actually think that has some useful consequences. The present really does matter quite a bit in playoff baseball – more than the future, and certainly more than the past. But it’s also caused them plenty of problems. The clearest example is also the most notable move Weiss has made so far. The Braves deployed bullpen games in each of the first two games of the NLDS over the weekend. The first was unavoidable, a consequence of their injury-depleted rotation, but the second was the direct consequence of Weiss’ earlier actions.

I’m talking about Chris Sale, of course. Sale started the Wild Card opener against the Phillies last Tuesday and worked into the seventh, throwing 95 pitches before departing with two on, one out, and the bottom of the Philly lineup coming to the plate. After a little turbulence (Didier Fuentes allowed both inherited runners to score, giving the Phillies the lead), the Braves pulled it out. But after Philadelphia won the second game of the series, Weiss called on Sale to cover the final four outs of the decisive Game 3. Read the rest of this entry »

Ty France fell just short of playing the hero during the ninth inning of Saturday night’s Division Series opener between the Padres and Brewers, and his performance on Sunday at the center of the San Diego offense would have loomed larger if not for Mason Miller’s ninth-inning meltdown. The 32-year-old first baseman has been swinging a hot bat during the postseason, building on an impressive campaign in which he returned to the team that drafted him in 2015 and rediscovered his swing after two years of meandering around replacement level and through the rosters of four teams.

France collected two of the Padres’ five hits in Game 2 and drove in two of their three runs. He put them on the board in the first inning against starter Logan Henderson, ripping a 104.3-mph RBI single to right-center after Manny Machado worked a two-out walk and then took second on a wild pitch. After striking out in the third and being hit on the elbow guard by a Henderson changeup in the sixth, France faced Abner Uribe in the seventh with the Padres up 2-1 and Fernando Tatis Jr. (who had reached on an error) on second and Machado (who had walked again) on first. Ahead in the count 1-0, he smacked a 101.3-mph grounder to right field. Tatis raced home to run the score to 3-1, but Sal Frelick threw Machado out at third base to extinguish the rally.

Alas, the Padres couldn’t hold their two-run lead. The Brewers clawed back a run in the bottom of the seventh with a single, a walk, and a throwing error by second baseman Jake Cronenworth, then rallied for two in the ninth as Miller walked three before surrendering a walk-off single to Jackson Chourio. Read the rest of this entry »

Over the weekend, I graded the managerial performances of the two National League managers eliminated in the Wild Card round. Now, it’s on to the American League. Both Joe Espada’s Astros and Chad Tracy’s Red Sox lasted just two games in the playoffs and didn’t even make it to October, but each still had plenty of decisions to make in their 18 innings at the postseason helm.

I went over this in the NL rundown, but I’ll say again that like Ben Clemens, who originated this series, I care about process and not results here. It’s easy to say “that was a great move because it worked” or “that was a bad move because it failed,” but managers obviously can’t know the result of their decision as they’re making it. I’ve tried my best to transport myself back to the moment of each decision — taking into account the pitches, innings, and plate appearances that led up to it — while ignoring the outcomes.

Before we begin, I’ll also reiterate that while these are ostensibly manager report cards, there’s a much larger group of people behind the manager that helps to inform his decisions. Before the game, that includes discussions with the front office, which provides the reams of data that every manager has at his disposal during play; in-game, he’s getting feedback from his coaching staff and players on their levels of health and readiness. It really does take a village to get through a baseball game, and realistically, the praise and scorn doesn’t belong to the manager alone.

Let’s get into it.

Joe Espada

Batting: Incomplete

None of the managers who lost in the Wild Card round made fewer changes than Espada, who pinch-hit just once in two losses to the White Sox. That one substitution worked brilliantly, with righty Nelson Velázquez hitting for lefty Taylor Trammell against southpaw Sean Newcomb and promptly homering to give the Astros their first two runs of Game 1. That was a no-brainer of a decision for a team that needed runs; Velázquez had an 88 wRC+ against lefties this year to Trammell’s horrendous 12.

Espada’s ability to go to his bench was hamstrung in Game 2, as right knee soreness incurred in Game 1 limited Isaac Paredes to DH duty and forced Nick Allen into the starting lineup at third base. Letting Allen hit in the fifth inning down by a run with a runner on first and one out was understandable. Using a bat like Trammell or Joey Loperfido would have forced Raynel Delgado into the game at third, and no matter the leverage of the situation, Espada would have had to pinch-hit for him when his spot came up, with no backup infielders left at that point.

The overall lack of offensive mixing-and-matching from Espada was more of a roster construction problem than a manager issue, as was the club’s batting order. Espada’s lineup created a pocket of righties from spots three through six, with Yordan Alvarez batting second as the only hard-hitting lefty to plan around. Still, he really couldn’t have put his lineup together any better given the cards he was dealt.

Pitching: C+

When grading the Wild Card managers, I’ve tried to be sympathetic to those without much to work with, and that was absolutely the case for Espada and his pitching staff. I wouldn’t wish a Game 1 bullpen game on a manager even if he was my worst enemy, and especially not one with Houston’s pitching staff. And given that the Astros clinched on the last day of the season, they couldn’t have lined the pitching up any differently, either. But while a bullpen game was necessary, starting the game with AJ Blubaugh on the mound wasn’t.

Blubaugh, who led all relievers in innings pitched this year with 96, was an unsung hero for the Astros during the regular season. But his 2026 was marked more by quantity than quality; his 3.66 ERA outpaced his 4.25 xERA and 4.31 FIP, and he limped to the finish line with 10 runs allowed in his last 10 appearances. Fellow righty Miguel Ullola finished his season stronger and could have provided length similar to the best version of Blubaugh (as he showed later in the game). Or, given the White Sox’s penchant for aggressive in-game platooning, going with a lefty like Josh Hendrickson, Bennett Sousa, or Bryan King may well have forced White Sox manager Will Venable into aggressively substituting once a lefty was out of the game. That might have led to Randal Grichuk starting the game with the platoon advantage and then being pinch-hit for as soon as Espada brought in a righty. Once that happened, Espada would have had a clearer lane of lefty bats to manage against, allowing him to use a second lefty pitcher like Hendrickson, Sousa, or King. Venable may well have countered with someone like Tommy Pham, but getting Grichuk’s lefty-mashing bat out of the game after a single plate appearance would’ve been a big win.

Espada managed from behind for the rest of the game, and once Blubaugh exited, all of his decisions were logical but came too late for the offense to recover. King ended up with a logical pocket of four lefties in six batters before turning the ball over to Ullola, who was a godsend, providing length without Espada having to worry about left-right matchups. Once Ullola was done, it was the standard manager playbook of alternating lefties and righties to play matchups, before giving the ball to his highest-leverage arms in Bryan Abreu and Josh Hader in the eighth and ninth. Houston was down by four runs when Abreu entered and by three runs when Hader came in, but in a best-of-three series, chasing a Game 1 win by using your best arms is what I would have done, too.

Game 2 could not have started more disastrously, with the Astros’ best starter, Hunter Brown, unable to make it out of the first inning. While he was let down by his defense and didn’t pitch quite as badly as his line would suggest, I understand Espada’s urgency in pulling the plug and making it a second straight bullpen game. But Blubaugh again being the first reliever out of the ‘pen was puzzling, and my evaluation doesn’t care that it happened to work out. This was another chance for Espada to bring in a southpaw against a lineup with five lefties in its first six spots, and yet Blubaugh was called upon to face Sam Antonacci and the top of the White Sox lineup for the second time in two days. Doubling down by sending Blubaugh back out for the second was equally perplexing, especially with Peter Lambert available for length.

After the second inning, however, I thought Espada redeemed himself with a near-perfect set of moves given his personnel. Lambert was the best arm available for the middle frames, and with very few trusted arms on staff, I’m giving his manager a pass for allowing him to face more than nine hitters. Batters 10 and 11 drawing walks made it Bryan Abreu time in the sixth with nobody out, again the appropriate move given that the Astros were down by one at the time and it was a must-win game. Abreu is no stranger to coming in and cleaning up messes, and while Chase Meidroth took him deep, he carved through eight outs thereafter before turning the ball over to Hader for four outs.

After Meidroth homered, the Astros trailed by four for the remainder of the game, and knowing that the Astros would need Hader for a third straight game if they miraculously pulled off a Game 2 comeback, I think Espada struck the right balance between getting Hader into the game and being cognizant that he’d need his closer the next day. With the benefit of hindsight, that exposes the danger of chasing a comeback by using Hader in Game 1 — and I certainly wouldn’t have liked using him in that game if the Astros were down four or five — but as I’ve mentioned repeatedly during these report cards, the manager can’t know the future. The best chance of pulling out win in a Game 1 that was still within striking distance comes by using Hader in the ninth, and the same is true for a Game 2 comeback.

Chad Tracy

Batting: Incomplete

Tracy entered the Wild Card Series with his healthiest and most complete offense of the season, and he lined things up about as well as you can against a tough customer like Cam Schlittler in Game 1. The Yankees used two righties in relief of Schlittler, and the only move Tracy made was to pinch-hit Andruw Monasterio for the injured Roman Anthony in the sixth, with Schlittler still in the game.

Anthony was removed from the roster prior to Game 2 due to his hand injury, and the combination of that and a tough opposing lefty in Max Fried led to a very different lineup for Boston, though one that I also didn’t have any problems with. Tracy’s one pinch-hit move of the night was playing the platoon game by swapping Nate Eaton out for Jarren Duran against Will Warren in the eighth. There weren’t many moves, hence the incomplete, but the ones he made were good.

Pitching: C

Out of the eight grades I’ve given to the managers eliminated in the Wild Card round, this was the toughest one to sort out. In a nutshell, I loved what Tracy did with his starting pitchers and strongly disliked which relievers he chose to deploy when.

Payton Tolle faced 19 batters in his Game 1 start, and was presumably allowed to face Paul Goldschmidt for a third time because Tracy would’ve rather had that matchup than likely pinch-hitter Luis García Jr. against a righty pitcher. That allowed Tracy to deploy lefty Erik Miller against Ben Rice… which immediately backfired, as Rice homered. Still, I have no problem with that choice. Rice was worse against lefties this year, and while Miller struggled in September, I understand going with the big stuff against Rice’s big swing. The bullpen arms used after Miller, though, represented baffling choice after baffling choice.

Still down just two runs, Tracy used lower-leverage arms Greg Weissert and Alec Gamboa, with Gamboa, Wyatt Olds and Brayan Bello allowing the Yankees to blow the game wide open on their way to a 9-0 drubbing. In a postgame exchange with the Boston Globe’s Tim Healey, Tracy defended using the pitchers he did — thereby lowering his win probability for that game compared to using better arms like Garrett Whitlock or Aroldis Chapman — as being a consequence of an offense that was, in his estimation, unlikely to come back no matter who pitched.

While I understand taking the long view of potentially needing to play three games in three days, if you aren’t going to chase a win down two runs with Schlittler soon to come out of the game, when are you going to chase a win? A manager can only manage the game in front of him, and for all Tracy knew, the Red Sox could end up winning Game 2 without needing Whitlock or Chapman anyway.

Game 2 ended up having a similar inflection point, with starter Sonny Gray pulled after just 70 pitches and 19 batters. That led to quite the anti-analytics firestorm on social media, but here in my corner of the internet, removing Gray was a clear-cut decision. I don’t care about Gray’s third-time-through-the-order performance being really good this season; he was bad in that scenario last year, and the third-time-through penalty is always going to exist to at least some extent. Gray had also allowed four of the last eight batters to reach and was clearly losing effectiveness. But giving Cody Bellinger another look at Miller a day after the lefty’s own ineffectiveness wasn’t ideal; unless Garrett Crochet was completely uncomfortable coming in with runners on base, I’d have preferred him in that scenario.

Instead, Crochet came in to start the following inning and the game went sideways from there. Spencer Jones reached on a strikeout-wild pitch and the inning spiraled thereafter, and while it wasn’t all Crochet’s fault, his performance all but assured a loss. Tracy then proved my earlier point about not knowing what the next day’s game will hold by using Whitlock down two runs with the bases loaded in the sixth and Chapman down seven runs in the eighth. Using Whitlock there was a coherent attempt to keep the game close, while Chapman was a “well, we need a miracle” pitching change. Had the Red Sox used Chapman and Whitlock to chase a win in Game 1 and ultimately won, Chapman never would’ve pitched down seven runs in Game 2, since Game 3 would be on the horizon. In sum: Yes, it matters when there’s a game tomorrow, but tomorrow’s game can go any which way. If you’re only down a couple runs and have a rested leverage arm, use him.

Cam Schlittler threw the Red Sox a curveball in Game 1 of the AL Wild Card Series. Well, actually, he threw them a lot of curveballs — 32, to be exact.

In the Yankees’ resounding 9-0 win over their archrivals last week at Yankee Stadium, the 25-year-old flamethrower went 6 1/3 scoreless innings, giving up just two hits and one walk while striking out 10 and throwing a career-high 117 pitches. Except for the pitch count, his final line reflects the same dominance we’ve seen repeatedly throughout a 2026 season in which Schlittler went 14-6 with a 1.95 ERA, a 2.56 FIP, and 6.2 WAR across 193 2/3 innings. The difference this time was how he got there, and it poses a new challenge for opposing batters when he starts against the Rays in Game 2 of the ALDS on Monday night at Tropicana Field.

Schlittler turned to the curveball early and often, utterly baffling a Boston lineup that was geared up for his signature three-fastball repertoire. Instead, they got a heavy dose of the hook and couldn’t handle it. In Game 1, he threw his curveball 27.4% of the time. The Red Sox swung at 16 of the 32 curves they saw from Schlittler, whiffing on eight of them, fouling off six, and putting two in play; the first of those two fair balls was a softly hit lineout to shortstop in the fifth inning, while the second came when Wilyer Abreu lined the right-hander’s last pitch of the game to right field for a single. Four of Schlittler’s 10 strikeout pitches were curveballs, all during his first time through the order. Read the rest of this entry »

Direct links to applications (please see job details below):

Data Scientist
Intern, Data Science
Associate Analyst, Baseball Analytics: Integration
Associate Hitting Analyst, Baseball Analytics
Associate, Video & Technology (International Scouting)
Senior Data Scientist, Baseball Analytics

Data Scientist

Location: Citi Field – Queens, New York

Summary:

The New York Mets are seeking a Data Scientist in Baseball Analytics. The Data Scientist will build, test, and present statistical models that inform decision-making in all facets of Baseball Operations. This position requires strong background in complex statistics and data analytics, as well as the ability to communicate statistical model details and findings to both a technical and non-technical audience. Prior experience in or knowledge of baseball is a plus, but is not required.

Essential Duties & Responsibilities:

• Build statistical models to answer a wide variety of baseball-related questions affecting the operations of the organization using advanced knowledge of statistics and data analytics and exercising appropriate discretion and judgment regarding development of statistical models
• Interpret data and report conclusions drawn from their analyses
• Present model outputs in an effective way, both for technical and non-technical audiences
• Communicate well with both the Baseball Analytics team as well as other Baseball Operations personnel to understand the parameters of any particular research project
• Provide advice on the desired outputs from the data engineering team, and guidance to the Baseball Systems team on how best to present model results
• Evaluate potential new data sources and technologies to determine their validity and usefulness
• Consistently analyze research in analytics that can help improve the modeling work done by the Baseball Analytics department

Qualifications & Requirements:

• Masters and/or BS degree in statistics or a related field
• Professional experience in a quantitative position is a plus
• Strong background in a wide variety of statistical techniques
• Strong proficiency in R, Python, or similar, as well as strong proficiency in SQL
• Basic knowledge of data engineering and front-end development is a plus, for the purpose of communicating with those departments
• Strong communication skills
• Ability to work cooperatively with others, and to take control of large-scale projects with little or no daily oversight

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets value the unique qualities individuals with various backgrounds and experiences can offer the organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

Salary Range: $80,000 – $100,000

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

Intern, Data Science

Location: Citi Field – Queens, New York

Summary:

The New York Mets are seeking an intern in our Baseball Analytics Department for the summer of 2027. During the summer, the Intern will build, test, and present statistical models to inform the decision-making of our Baseball Operations department. This position requires strong background in complex statistics and data analytics, as well as the ability to communicate statistical model details and findings to both a technical and non-technical audience. Prior experience in or knowledge of baseball is a plus, but is not required.

Essential Duties & Responsibilities:

• Build statistical models to answer a wide variety of baseball-related questions affecting the operations of the organization using advanced knowledge of statistics and data analytics and exercising appropriate discretion and judgment regarding development of statistical models
• Interpret data and report conclusions drawn from their analyses
• Present model outputs in an effective way, both for technical and non-technical audiences
• Communicate well with both the Baseball Analytics team as well as other Baseball Operations personnel to understand the parameters of any particular research project

Qualifications:

• Pursuing a degree in statistics or a related field
• Professional experience in a quantitative position is a plus
• Strong background in a wide variety of statistical techniques
• Strong proficiency in R or Python
• Strong communication skills
• Ability to work cooperatively with others

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets recognize the importance of a diverse workforce and value the unique qualities individuals of various backgrounds and experiences can offer to the Organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

Pay Range: $20.00 – $25.00/hour

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

Associate Analyst, Baseball Analytics: Integration

Location: Citi Field – Queens, New York

Summary:

The New York Mets are seeking an Associate Analyst to join the Baseball Analytics: Integration team. In this role, you will help Baseball Operations answer the wide range of questions that arise throughout the year, taking on fast-moving projects that touch many areas of the organization. This is an opportunity to apply quantitative skills to meaningful baseball decisions, gain broad exposure to how a Major League organization operates, and work closely with colleagues across a variety of functions.

Essential Duties & Responsibilities:

• Translate questions from across Baseball Operations into clear research and analytical approaches
• Retrieve, combine, clean, and validate data from internal databases and relevant public sources
• Conduct timely research and analysis across multiple concurrent, short-term projects, using statistical methods or modeling when appropriate
• Communicate findings through concise, easy-to-understand reports, visualizations, and messages
• Collaborate with Data Engineering and Systems teams to turn analytical work into reliable, accessible data and tools for use across Baseball Operations
• Maintain clear, reproducible code and documentation, and develop reusable processes for recurring analytical needs

Qualifications:

• Bachelor’s degree in a quantitative field, or equivalent experience
• Experience using R, Python, or a similar analytical programming language
• Proficiency in SQL, including joining, filtering, aggregating, and validating data
• Strong analytical and problem-solving skills
• Attention to detail, particularly when reviewing data and analytical outputs
• Ability to organize work, manage competing priorities, and meet deadlines
• Strong verbal and written communication skills

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets value the unique qualities individuals with various backgrounds and experiences can offer the organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

Pay Range: $22.00 – $25.00/hour

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

Associate Hitting Analyst, Baseball Analytics

Location: Citi Field – Queens, New York

Summary:

The Associate Hitting Analyst will develop high-impact analytical tools and systems that advance hitting evaluation and drive optimization and improvement strategies across internal player development and external player acquisition. This individual will lead research, monitor performance trends, and collaborate across departments to uncover actionable opportunities that deepen organizational hitting knowledge and strengthen decision-making in both the acquisition and development spaces of Baseball Operations.

Essential Duties & Responsibilities:

• Analyze new data sources and their potential to explain performance
• Communicate research to on-field staff and Player Development leadership, translating complex concepts into clear recommendations
• Transform internal data and model results into actionable information that enhances both in-game and player performance strategy
• Collaborate with Biomechanics and Performance teams to analyze players’ physical capabilities
• Systematically identify internal and external players with room for improvement
• Work with Data Science team to understand how players’ capacity to improve impacts their value
• Perform research that explains how players are able to express skills on the field
• Expand the organization’s understanding of how players can improve relative to expectations

Qualifications & Requirements:

• Creativity and curiosity regarding the game of baseball
• Statistical modeling experience. Experience in Biomechanics is a plus
• Knowledge of baseball technology, including but not limited to KinaTrax, Blast Motion, Hawk-Eye, and force plates
• Ability to collaborate and work within and across teams
• Strong verbal and written communication skills
• Demonstrated ability to manage multiple projects simultaneously and execute tasks under time constraints
• Interest in public baseball research
• Experience in R, Python, or similar programming languages, and proficiency in SQL
• Must be able to work unconventional hours and travel

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets value the unique qualities individuals with various backgrounds and experiences can offer the organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

Pay Range: $22.00 – $25.00/hour

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

Associate, Video & Technology (International Scouting)

Location: New York Mets Complex – Dominican Republic

Summary:

The Associate, Video & Technology (International Scouting) will execute the day-to-day on field video capture, data collection, and technology operations across international amateur showcases, partner programs, and academy tryouts in the Dominican Republic. This individual will serve as the field-level technical hub for the international scouting department—operating portable tracking hardware, capturing standardized scouting video, organizing and tagging digital assets, and syncing data with internal platforms.

Operating in a high-stakes, fast-moving evaluation environment, this role demands absolute confidentiality, meticulous attention to detail, operational problem-solving in challenging outdoor field environments, and proactive collaboration with area scouts, international crosscheckers, and front-office decision-makers.

Essential Duties & Responsibilities:

• Field Technology Operations: Set up, calibrate, operate, and troubleshoot portable ball-tracking and bat-tracking technology (e.g., TrackMan Portable, Blast Motion, portable force plates, high-speed cameras) at amateur showcases, private workouts, and academy games
• Scouting Video Capture & Ingestion: Film hitters, pitchers, and defensive drills adhering strictly to organizational filming standards. Accurately tag, trim, log, and ingest video into internal proprietary athlete management databases on daily turnaround times
• Data Quality Control & Reporting: Maintain meticulous quality control over captured data feeds. Making sure the tagged information is accurate before submitting it to the internal platform
• Territory Coverage & Scouting Logistics: Travel across key Dominican scouting circuits (e.g., San Cristóbal, Boca Chica, San Pedro de Macorís, Santiago, Baní, and Santo Domingo), coordinating directly with the DR Video Tech Coordinator along with the DR Scouting Supervisor and Area Scouts to align technical coverage on a daily basis
• Technology Asset Management: Clean, charge, pack, transport, and maintain all mobile hardware, tablets, cameras, tripods, and other tech, ensuring zero downtime during showcases and events
• Cross-Departmental Collaboration: Assist visiting international crosscheckers, analytical evaluators, and scouting executives by providing real-time data feeds
• International Travel Support: As needed, deploy to international scouting assignments outside the Dominican Republic to support tournament coverage and data intake

Requirements:

• Driver’s License & Reliable Transportation: Valid Dominican driver’s license, a clean driving record, and daily access to an insured, reliable vehicle capable of transporting equipment across varying road conditions throughout the island
• Travel & Schedule Flexibility: Willingness and capability to travel extensively across the Dominican Republic, with readiness to travel abroad. Ability to work unconventional hours, including early mornings, weekends and late hours as needed according to the workload
• Technical Savvy & Computer Proficiency: Proficiency with Microsoft Excel, general PC operating systems, tech saavy experience to handle distinct software
• Baseball Technology Familiarity: Demonstrated working knowledge of baseball tracking technology (TrackMan, Hawk-Eye, FlightScope, Blast Motion, Rapsodo, or related optical/radar systems) and high-frame-rate sports cameras
• Bilingual Communication: Professional proficiency in both Spanish and English (spoken and written), enabling seamless coordination between Latin American trainers/players and US-based front oAice personnel
• Discretion & Confidentiality: Absolute integrity and commitment to organizational secrecy regarding prospect evaluations, proprietary metrics, acquisition targets, and internal strategy
• Physical Demands: Ability to carry 40–50 lbs of hardware/tripods and stand outdoors in high-heat and humid conditions for extended periods

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets value the unique qualities individuals with various backgrounds and experiences can offer the organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

Senior Data Scientist, Baseball Analytics

Location: Citi Field – Queens, New York

Summary:

The New York Mets are seeking a Senior Data Scientist in Baseball Analytics. The Senior Data Scientist will build, test, and present statistical models that inform decision-making in all facets of Baseball Operations. This position requires strong background in complex statistics and data analytics, as well as the ability to communicate statistical model details and findings to both a technical and non-technical audience. Prior experience in or knowledge of baseball is a plus, but is not required.

Essential Duties & Responsibilities:

• Build statistical models to answer a wide variety of baseball-related questions affecting the operations of the organization using advanced knowledge of statistics and data analytics and exercising appropriate discretion and judgment regarding development of statistical models

• Interpret data and report conclusions drawn from their analyses

• Present model outputs in an effective way, both for technical and non-technical audiences

• Communicate well with both the Baseball Analytics team as well as other Baseball Operations personnel to understand the parameters of any particular research project

• Provide advice on the desired outputs from the data engineering team, and guidance to the Baseball Systems team on how best to present model results

• Assist with recruiting, hiring, and mentoring new analysts in the Baseball Analytics department

• Evaluate potential new data sources and technologies to determine their validity and usefulness

• Consistently analyze recent research in analytics that can help improve the modeling work done by the Baseball Analytics department

Qualifications:

• Ph.D. in statistics or a related field, or equivalent professional experience

• Strong background in a wide variety of statistical techniques

• Strong proficiency in R, Python, or similar, as well as strong proficiency in SQL

• Basic knowledge of data engineering and front-end development is a plus, for the purpose of communicating with those departments

• Strong communication skills

• Ability to work cooperatively with others, and to take control of large-scale projects with little or no daily oversight

The above information is intended to describe the general nature, type, and level of work to be performed. The information is not intended to be an exhaustive or complete list of all responsibilities, duties, and skills required for this position. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time. The individual selected may perform other related duties as assigned or requested.

The New York Mets recognize the importance of a diverse workforce and value the unique qualities individuals of various backgrounds and experiences can offer to the Organization. Our continued success depends heavily on the quality of our workforce. The Organization is committed to providing employees with the opportunity to develop to their fullest potential.

Salary Range: $120,000 – $150,000

For technical reasons, we strongly advise to not use an .edu email address when applying. Thank you very much.

To Apply
To apply, please follow this link.

The content in this posting was created and provided solely by the New York Mets.

Heading into Game 2 of the NLDS, much of the talk was of the mismatch in pitching rotations between the Dodgers and the Braves, and whether Atlanta’s bullpen could continue to cover up for a rotation held together with rubber bands and duct tape. Yet, in the end, it was the Dodgers who ended up burning the most relievers, and the denouement was only in doubt because the Braves missed a few opportunities to blow the game, a 3-2 win, wide open.

The most-talked-about pitching decision was probably the one made before the game started: Going with a third consecutive bullpen game rather than starting ace Chris Sale in Game 2. It’s a decision that Walt Weiss clearly doesn’t regret, at least not when speaking in public. He told reporters:

“We had a conversation this morning. Look, at the end of the day, we want full-strength Chris Sale. I know him at 80 percent is really good, but that’s what it came down to. We’ve given him extra rest all year, and it’s served him very well. It allowed him to do what he did the other night, I think all the extra rest he’d gotten. He’d be on normal rest from his last start, but he had the outing in between. Not sure you’re getting the best version of him pitching today. We’re certain he will pitch in Game 3.

Read the rest of this entry »