Job Posting: Dodgers Baseball R&D Quantitative Analyst
Position: Quantitative Analyst, Baseball Analytics
Department: Baseball Research & Development
Description:
The Los Angeles Dodgers seek a full-time, entry-level analyst for the team’s Baseball Analytics group. Their objective is to identify highly talented, mathematically-oriented candidates as they build an industry-leading analytics team.
Job Functions:
- Statistical modeling and quantitative analysis to support one or more research projects focused on player evaluation/development and strategic decision-making
- Developing, automating, and implementing mathematical, statistical, and/or machine learning models
- Preparing reports and presentations to disseminate model results to front office, coaching staff, player development, scouting, and medical/performance staff
- Performing ad hoc data analysis to support Baseball Operations
- Other duties and responsibilities as assigned
Basic Requirements and Qualifications:
- B.S. in mathematics, statistics, computer science, operations research, or a related quantitative field
- Experience building and validating mathematical, statistical, and/or machine learning models, preferably in Python or R
- Some computer programming experience
- Familiarity with SQL
- Knowledge of recent advances within the public baseball research community
- Desire to work in a collaborative team environment
You should apply if:
- You want to help the Dodgers build an industry-leading analytics team
- You love to compete, and you want to see the impact of your work on the field and in the box score
When you apply for this job online, please include answers to following questions in your cover letter, using 500 words or fewer:
- When are you available to start?
- Why are you interested in pursuing this opportunity?
- What experience do you have building mathematical and/or statistical models?
- Additionally, if you are or were enrolled in a university degree program (within the last three years), please include with your application a complete list of the technical courses that you have taken or in which you are currently enrolled, along with course numbers and grades.
To Apply:
Qualified candidates should submit a cover letter and resume online at www.dodgers.com under Job Opportunities. The deadline for applications is November 9, 2018.
Meg is the editor-in-chief of FanGraphs and the co-host of Effectively Wild. Prior to joining FanGraphs, her work appeared at Baseball Prospectus, Lookout Landing, and Just A Bit Outside. You can follow her on Bluesky @megrowler.fangraphs.com.
Must NOT be able to communicate in Spanish.
There is no mention of having a solid understanding of the GAME of baseball; its rules, strategies, how real teams are put together, how MLE’s work, baseball history, etc. That seems rather strange.
Yea, because a guy who models pitches and predicts how to increase movement based on changes in spin axes needs to know history of the game and how “real teams” work.
FYI, real teams use quants. Those who don’t believe that are ignorant to analytics.
Right because knowing how a pitcher holds a baseball has no bearing on changing spin axis. This is more about the physics of baseball and bio-mechanics than knowing how to program in Python or R. Having some real world knowledge of baseball I believe would help. Or else you end like the situation I was in a last year where I had to teach a young mechanical engineer the basics of manufacturing because their design that looked great in CAD was basically un-manufacturable. Theory is foundational. It’s even better when tied to real world understanding and understanding the limitations of the real world.
They already have department heads and leaders who understand those things
Get the best talent, they can learn baseball