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Job DescriptionAs a Lead/Senior Quantitative Analyst, Predictive Modeling, you help shape the future of Phillies Baseball Operations by building statistical models to forecast player performance and communicating those results to decision-makers. Using analytical rigor and sophisticated statistical modeling techniques, you identify opportunities for the Phillies to improve via the application of forecasts to player development and evaluation. Join a team doing cutting-edge foundational research on biomechanics, human movement, ball-flight physics, and more, with the unique opportunity to apply those findings to player evaluation.
Responsibilities
Conduct and oversee statistical forecasting projects in multiple baseball subject areas
Collaborate with baseball subject matter experts in scouting, development, biomechanics, machine learning, decision science, and more, integrating their expertise into player evaluation models
Maximize organizational impact of the department’s player evaluation models by advocating model-driven decision-making in various baseball contexts
Ensure projects conform to best practices for implementing, maintaining, and improving predictive models throughout their life cycles
Assist and mentor other members of the QA team with their projects by providing guidance and feedback on your areas of expertise within baseball and statistical modeling
Continually enhance your and your colleagues’ knowledge of baseball and data science through documentation, reading, research, and discussion with your teammates and the rest of the front office
Required Qualifications
2-5+ years of relevant work or graduate school experience
Possess or are pursuing a BS, MS or PhD in Statistics or related (e.g., mathematics, physics, or ops research) or equivalent practical experience
○ To determine leveling we look at a variety of factors including, but not limited to,
years of experience and education. Typically we consider candidates as Lead QA around 2-3 years of experience and Senior QA around 4-5+ years of experience
Proficiency with scripting languages such as Python, statistical software (R, S-Plus, SAS, or similar), and databases (SQL)
Demonstrated experience designing, constructing, implementing, and leading technical research projects for use by non-technical stakeholders
Proven willingness to both teach others and learn new techniques
Willingness to work as part of a team on complex projects
Proven leadership and self-direction
Preferred Qualifications
Experience with a probabilistic programming language (Stan, PyMC, etc.)
Experience managing or overseeing the work of other data scientists or analysts
Experience with model-driven decision-making under uncertainty (eg. a rigorous approach to fantasy sports, poker, etc.)
Interested applicants should submit both their resume and an answer to the following question:
The R&D department has been asked to identify the best defensive center fielder in baseball. What models would you build to answer that question, and how would you apply those models to decision-making? (250 word limit)
Tip: There’s no defined right or wrong answer. Responses are used to get some insight into how you approach problem solving and baseball in general.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.
