Senior Director of Analytics & Decision Science

Position Summary

The Senior Director of Competitive Analytics and Decision Science will serve as the embedded analytics partner to assist coaching and performance staff. Own the vision, architecture, and roadmap for unified athletic information systems that integrates departmental data into a single decision engine. Define how data flows across recruiting, compliance, NIL and revenue sharing, ticketing, development, academics, sports medicine, and finance to support decision‑making.

The core purpose of this role is to build and maintain statistical and machine‑learning models that directly inform on‑court and on‑field strategy, roster decisions, recruiting, and the allocation of competitive resources.

This is a hands‑on decision‑science role focused on competition. The Senior Director works shoulder‑to‑shoulder with coaches and performance staff to scope the questions that matter, builds the models and tools to answer them, and translates the results into clear, actionable recommendations.

• Bachelor's degree in a related field or equivalent plus 12 years of professional experience to include 5 years of supervisory experience

• Degree in statistics, data science, computer science, applied mathematics, economics, or a related quantitative field;
  Five or more years of experience in analytics or data science, including building and deploying models that informed real decisions.

• Demonstrated expertise building, validating, and maintaining statistical and machine‑learning models.
• Strong programming and data skills – e.g., Python or R, and SQL – and the ability to assemble and maintain the data needed for your own modeling work.
• Proven ability to translate technical analysis into clear, persuasive recommendations for coaches and non‑technical stakeholders.
• Strong collaboration skills and the credibility to embed with a coaching and performance staff.

• Partner directly with coaching and performance staff to scope the analytical questions that matter most.
• Build, validate, and maintain statistical and machine‑learning models that inform on‑court and on‑field strategy, roster decisions, recruiting, and resource allocation.
• Provide opponent scouting, self‑scouting, and tendency analysis to support game and match preparation.
• Develop in‑game and in‑match decision support, including situational, lineup, rotation, and play‑selection insights.
• Build player‑evaluation and roster‑construction models to support recruiting prioritization, talent projection, and roster decisions.
• Support practice planning and the allocation of competitive resources with data‑informed analysis.
• Translate complex analyses into clear, actionable recommendations that coaches and administrators can act on with confidence.

• Assemble, clean, and maintain the datasets, pipelines, and tools required for the analytical work – scoped to what the models need, not enterprise‑wide integration.
• Work within existing platforms and vendor relationships, partnering with athletics and university IT rather than directing a systems build‑out.
• Evaluate and recommend analytics tools and data sources that strengthen competitive modeling; surface needs to IT and leadership rather than owning procurement of enterprise systems.

• Develop dashboards, reports, and decision‑support tools tailored to coaching staffs and athletic leadership.
• Support roster and competitive‑resource allocation and performance evaluation with rigorous analysis.
• Proactively surface trends, risks, and opportunities relevant to competition through original analysis.

• Serve as the department's subject‑matter expert on competitive analytics and decision science.
• Help shape the department's approach to data‑informed competitive decision‑making.
• Recruit, mentor, and manage additional analysts as the function grows.
• Work closely with coaching, performance, and recruiting staff as the primary stakeholders for this role.
• Coordinate with IT, sports science,…