The Dodgers are famous around Major League Baseball for their ability to use data to create strategies that have led to seven straight post-season appearances.
Earlier today, the Dodgers President of Baseball Operations, Andrew Friedman told us that there are a lot of HR issues to take care of with a lot of the coaching staff being recruited by other teams in the league. Friedman also probably meant adding to the analytics team as the Director of Quantitative Analysis, Scott Powers just posted a job for an entry level position on the team:
The Baseball Analytics team of the Los Angeles Dodgers is responsible for developing novel statistical methodology to support decision-making throughout Dodgers baseball operations. We 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.
- 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
- 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 non-technical 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
Linkedin shows us that the estimated base salary starts around $81,500 but total compensation could be around $98,600 a year. All the basic benefits are included with medical, vision, dental, a 401(k) and Pension Plan.
Any of you baseball analytics fans out there interested?