Please note this posting contains multiple positions.

Position: Quantitative Analyst

Department: Baseball Research & Development
Status: Full-Time
Reports to: Director, Quantitative Analysis
Deadline: November 8, 2019

Description:
The Baseball Analytics team of the Los Angeles Dodgers is responsible for developing novel statistical methodology to support decision-making throughout Dodgers baseball operations. They are seeking to hire a Quantitative Analyst to join the team. As a member of the team, you will collaborate with experts (from statistics, computer science, biomechanics and other disciplines) who will challenge you to bring scientific rigor to your research. This position offers the opportunity to solve challenging problems in data science and ultimately see the impact of your work on the field.

Job Functions:

• Develop and implement novel mathematical models to answer research questions in player evaluation, player development and in-game strategy
• Productionize and maintain data science projects relied upon by the rest of the organization to support their decision-making processes
• Collaborate with team members to provide technical advice, learn from their expertise and integrate data science projects with each other
• Perform ad hoc data analyses to answer urgent questions from front office leadership and other groups within baseball operations
• Prepare presentations and reports to disseminate model results to the front office, as well as staff from coaching, scouting and player development
• Assist with and manage personnel-related manners, such as reviewing resumes, interviewing candidates and overseeing intern projects

Basic Requirements/Qualifications:

• Bachelor’s degree in statistics, computer science, mathematics or any other STEM field related to data science
• Proficiency in R or Python
• Understanding of Git version control for code development
• Ability to communicative effectively in speech and in writing on a technical and nontechnical level
• Experience applying one or more of the following modeling techniques (or similarly specialized techniques) to real-world data preferred:
• Advanced statistical models such as generalized linear mixed models (GLMMs), spatial or time series models, or Bayesian hierarchical models
• Topics in machine learning (e.g. ensemble methods), artificial intelligence (e.g. reinforcement learning) or computer vision (e.g. pose estimation)
• Techniques from operations research such as optimization or simulation
• Experience with advanced data visualization libraries such as D3 or plotly preferred
• Experience maintaining a well-organized, well-documented code repository for productionizing a data science project preferred

To Apply:
To apply, visit https://www.mlb.com/dodgers/team/jobs.

Position: Quantitative Analysis Intern

Department: Baseball Research & Development
Status: Part-Time
Reports to: Director, Quantitative Analysis
Deadline: November 8, 2019

Description:
The Baseball Analytics team of the Los Angeles Dodgers is responsible for developing novel statistical methodology to support decision-making throughout Dodgers baseball operations. They are seeking to hire a summer intern to join the team. The primary goal of our internship program is to identify and develop talented individuals who may be interested in joining the team full-time in the future.

Job Functions:

• Collaborate with the team to select one quantitative research project, and take that project from start to finish during the 12 weeks of the internship
• Meet front office staff, coaches, and scouts; and get exposure to various aspects of baseball operations

Basic Requirements/Qualifications:

• Pursing a degree in statistics, computer science, mathematics or any other STEM field related to data science
• Experience with R or Python
• Ability to communicative effectively in speech and in writing on a technical and nontechnical level
• Experience with advanced statistical models such as generalized linear mixed models (GLMMs), spatial or time series models, or Bayesian hierarchical models preferred
• Experience with machine learning (e.g. ensemble methods), artificial intelligence (e.g. reinforcement learning) or computer vision (e.g. pose estimation) preferred
• Experience with operations research topics such as optimization or simulation preferred
• Experience with advanced data visualization libraries such as D3 or plotly preferred
• Experience maintaining a well-organized, well-documented code repository for productionizing a data science project preferred

To Apply:
To apply, visit https://www.mlb.com/dodgers/team/jobs.

The content in this posting was created and provided solely by the Los Angeles Dodgers.