Data Science Manager, Football

About the Role & Team

We are looking for a Data Science Manager to lead a team of data scientists The Data Science team here at Penn is responsible for building models, forecasts, and simulations to help improve theScore Bet and ESPN Bet products. Our team values creativity, collaboration, ingenuity, and ownership. We are looking for someone who is interested in joining a team building and enhancing an industry leading football (NFL / NCAAFB) model for theScore Bet and ESPNBet football product. This position is a rare opportunity enabling a highly motivated candidate to make a significant impact on an enterprise grade football data product.

About the Work

• Help identify and prioritize impactful data science projects as well define goals & objectives for the team.
• Manage and mentor team members as they progress through their career progression journey.
• Own decisions for Data Science project prioritization, roadmap, workflows, tooling, integrations, modeling techniques, algorithm, deliverables, etc.
• Subject Matter Expertise: Be the football subject matter expert for your teamto ensure data-driven solutions are in-line with sport-specific best practices
• Betting Expertise: Knowledge of the sports betting industry and demonstrated experience using football data to solve pricing problems
• Machine learning & statistical modeling: we want to be able to predict the likelihood or expected outcome of various events across different sports.
• Predictive & Prescriptive Analytics: we want to share in-depth knowledge on how our features are working and our forecasts are performing.
• Own relationships & touchpoints with primary stakeholders for each project in flight / on the roadmap & in production.
• Responsible for monitoring stability and accuracy of data science projects in production.
• Interact regularly department leaders; proactively initiate ideas to improve services or products; contribute to department or group objectives, strategy and priorities.
• Partner cross functionally with key executive leaders within the organization to leverage data in new and innovative ways to drive actionable insights and business value.
• Develop best practices for our internal data processes that include model building, modeling techniques, improved latency and readability.
• Design and build new predictive models and optimization routines that have an enterprise level impact. This varies from modeling expected sporting outcomes at an event level to utilizing various game state data to simulate full spectrums of expected outcomes.
• Write and maintain technical design and git/confluence documentation.
• Other duties as required.

About You

• Expert-level skills in solving quantitative problems with NFL and/or NCAAFB data & using sports data to solve pricing problems.
• A passion for sports and sports betting
• A Strong grasp of sports betting terminology, the sports betting industry, and betting specific data sources
• A deep understanding of utilizing sport-specific problem-solving techniques to model various elements of the game.
• A deep understanding of utilizing player and ball tracking data and enriched NFL and/or NCAAFB play-by-play data to solve football problems and how to utilize model predictions to augment various forecasts.
• Knowledge of best practices in dynamically projecting various aspects of player and team performance.
• Strong grasp on the fundamentals of simulation modeling and latency reduction techniques.
• Previous experience leading a team either in football or in the sports betting industry
• Previous experience scaling an NFL and/or NCAAFB data product that provided demonstrable value
• Excellent written, communication, organization, and presentation skills.
• The ability to lead, mentor, and efficiently run a team of data scientists.
• Excellent critical thinking skills to enhance problem-solving techniques, ensure data products are incredibly resilient, and the ability to identify potential edge-cases
• Experience with being provided a high-level long-term objective and leading a team of data scientists to provide a solution.
• Experience working cross-functionally with engineering teams and provisioning services using GitHub.
• Strong experience with traditional DS tools and frameworks such as SQL, Pandas, Numpy, SKLearn etc.
• Experience with any of Docker, Kubernetes with Terraform, Cloudwatch.
• Experience with DAG orchestration tools suchs as Argo Workflows, Step Functions, Cloud Fucntions, Dagster, Airflow, etc.
• Significant experience with AWS/GCP.

Nice to Have

• Familiarity with MLFlow.
• Experience setting up ML CI/CD pipelines, testing and validating code/data, managing databases, and deploying models.
• Experience with SKLearn, Tensorflow, PyTorch, Caffe, and/or Keras.
• Previous experience working in sports other than the NFL or NCAAFB

What We Offer

• Competitive compensation package
• Education and conference reimbursements
• Parental leave
• Opportunities for career progression and mentoring others

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