Senior Data Science Manager

You will lead a team of data scientists developing the next generation of Genius Sports’ market leading sports models. These models act as the sporting brain behind many of Genius’s customer facing products, calculating the probabilities of outcomes across a wide range of sports.

Forming part of a multi-disciplinary Agile team of Software Engineers, Data Scientists, QA Engineers and a Product Manager, you will look to work closely to the fundamental principles of continuous delivery and empowered, high-performing teams. We operate in a squad model to allow focus on the business top priorities, allowing exposure across multiple products while still maintaining strong ownership of your team’s domain.

As a Senior Data Science Manager, you will oversee the implementation of predictive models across many sports. You will lead your team in the development of algorithms to calculate the probabilities of sporting outcomes.

• Lead a specially formed, highly skilled team delivering an innovative & intelligent product!
• Work closely with a multi-disciplinary Agile team of Software Engineers, Data Scientists, QA Engineers and a Product Manager, adhering to the fundamental principles of continuous delivery and empowered, high-performing teams.
• Operate within a squad model to focus on business top priorities, gaining exposure across multiple products while maintaining strong ownership of your team’s domain.
• Tackle hard problems, collaborate with high calibre engineers and deliver smart solutions with an autonomous & performance focused approach that supports success, delivery & quality.
• Oversee the implementation of predictive models across many sports.
• Lead your team in the development of algorithms to calculate the probabilities of sporting outcomes.

• A BSc, MSc or PhD in Data Science, Mathematics, Computer Science, Computational Statistics, Machine Learning or other STEM subject (required)
• Strong leadership skills with a proven track record of successful delivery of high impact solutions to complex data science problems (required)
• Mentoring and Staff Development (required)
• Expert knowledge of probability and statistics (required)
• Expertise in a broad range of data science / machine learning algorithms (Monte Carlo simulation, neural networks, logistic regression, random forest, etc.) with a proven track record of delivering solutions to complex problems (required)
• Proficiency with Python or other scripting/programming languages (R, Matlab, etc) (required)
• Ability to bring clarity to complex domains, rapidly developing a deep understanding and challenging unclear requirements. You lead conversations that drive alignment and uncover edge cases others might miss (required)
• Familiarity with sports rules and strategies (football, American football, basketball, tennis, ice hockey, baseball, etc.) (required)
• Knowledge of Sports betting (preferred)
• Knowledge of Machine Learning Operations (MLOps) covering the full life cycle from model creation, deployment (Gitlab, AWS, Docker) and retraining (preferred)
• Knowledge of Data engineering (preferred)
• Knowledge of Rust, C++, other programming languages (preferred)
• Knowledge of Real-time systems and/or high-performance computing (preferred)
• Knowledge of Software System Design (preferred)
• Knowledge of Software Development Lifecycle (SDLC) (preferred)
• Curiosity and strong desire to learn and improve (required)
• Social skills, being able to act as a facilitator, can balance enabling others with individual contributions (required)
• Time management and asynchronous communication skills relevant for a geographically diverse engineering organization (required)
• Enthusiasm and ability to work collaboratively within a team (required)
• Excellent spoken and written English (required)
• Adherence to our core engineering principles of Aligned Autonomy, Psychological Safety and Continuous Improvement (required)

• A competitive salary and range of benefits
• Commitment to supporting employee wellbeing
• Opportunities to grow your skills, experience and career