Lead/Senior Quantitative Analyst, Predictive Modeling

Philadelphia Phillies - Baseball Operations • Philadelphia, PA

17h • Remote

About The Position

As 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.

Requirements

• 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
• 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

Nice To Haves

• 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.)

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree