Senior Director of Analytics & Decision Science

Senior Director of Competitive Analytics & Decision Science Posting Details

• Posting Number: S15466P
• Working Title:
  
  Senior Director of Competitive Analytics & Decision Science
• Department:
  Athletics-Business Office
• Employment Type:
  
  Employee
• Salary:
  Commensurate with experience
• Posting Date: 07/17/2026
• Closing Date: 09/01/2026
• Location:
  
  Athens, Georgia

The Senior Director of Competitive Analytics & 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 integrate 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 allocation of competitive resources.

• Partner directly with coaching and performance staff to scope the analytical questions that matter most and lead the development and delivery of the resulting models and tools.
• 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 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.
• Evaluate and recommend analytics tools and data sources that strengthen competitive modeling; surface needs to IT and leadership.
• Develop dashboards, reports, and decision‑support tools tailored to coaching staffs and athletic leadership.
• 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.
• Coordinate with IT, sports science, and other units to access data and tools, respecting each function’s ownership and expertise.
• Stay current on analytics methods used across professional and collegiate sport and bring the best of them into the program.
• Partner with IT to define how competitive analytics data can connect with other departmental data sources to support broader decision‑making.
• Advise on data standards, definitions, and quality practices that would make future integration smoother.
• Assist with evaluation of platforms and tools that support a more connected athletic information environment.

• 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 data needed for modeling.
• Proven ability to translate technical analysis into clear, persuasive recommendations for coaches and non‑technical stakeholders.
• Strong collaboration skills and credibility to embed with coaching and performance staff.

Minimum:

• Bachelor’s degree in a related field or equivalent plus 12 years of professional experience, including 5 years of supervisory experience.

Preferred:

• 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.