Senior Data Science Manager — Sports Analytics (Hybrid)

United States Digital Space LLC; Greater London; Hybrid; GBP 110,000 - 160,000; Full time

Benefits offered by this job

Hybrid working model

Competitive salary and benefits

Wellbeing support and growth

Job summary

Genius Sports is seeking a Senior Data Science Manager to lead a team developing predictive models across multiple sports. You will guide algorithms that calculate the probabilities of outcomes, collaborating in an Agile squad with engineers, data scientists, QA, and a Product Manager.

Ideal candidates have advanced degrees in data science or STEM, strong leadership, mentoring, and expert knowledge of probability, statistics, and ML methods.

Qualifications

• BSc/MSc/PhD in Data Science, Mathematics, CS, Computational Statistics or STEM
• Strong leadership with delivery of high-impact data science solutions
• Mentoring and staff development
• Expert knowledge of probability and statistics
• Expertise in ML algorithms (Monte Carlo, neural nets, logistic regression, random forest)
• Python or similar (R, Matlab)
• Ability to simplify complex domains and drive alignment
• Familiarity with sports rules and strategies across major sports

Responsibilities

• Oversee implementation of predictive models across many sports
• Lead team in development of algorithms to calculate probabilities of sporting outcomes
• Collaborate in Agile squad with software engineers, data scientists, QA, and PM
• Drive continuous delivery and high-quality solutions

Skills

Leadership

Probabilistic modeling

Mentoring

Statistics

ML algorithms

Python

Edge case analysis

Sports knowledge

Education

BSc/MSc/PhD in Data Science or STEM

Tools

Gitlab

AWS

Docker

Job description

Genius Sports is seeking a Senior Data Science Manager to lead a team developing predictive models across multiple sports. You will guide algorithms that calculate the probabilities of outcomes, collaborating in an Agile squad with engineers, data scientists, QA, and a Product Manager.

Ideal candidates have advanced degrees in data science or STEM, strong leadership, mentoring, and expert knowledge of probability, statistics, and ML methods.