Lead Data Science Engineer

1 month ago


London, Greater London, United Kingdom DraftKings Full time

We're shaping the future of sports and entertainment experiences at DraftKings. Our global team is pushing boundaries, developing cutting-edge products, and driving innovation in responsible gaming.

The Crown Is Yours

As a key member of our sports modelling team, you'll collaborate with data science technologists to create high-impact, best-in-class sports models that drive business growth.

Key responsibilities include:

  1. Designing and implementing data science applications in Python.
  2. Developing statistical and machine learning models and integrating them into data science applications.
  3. Contributing to the development of our MLOps pipeline.
  4. Data engineering of data assets to support data science application development.
  5. Writing production-quality code to deploy and run models in a sportsbook environment.
  6. Collaborating with product, developers, QAs, and delivery leads to move projects from ideation to development and deployment.
  7. Ensuring data flows work as expected and data science applications are well-integrated in the larger business context.
  8. Coaching and supporting junior data scientists within the team.

Requirements include:

  1. Experience as a data science expert, responsible for all aspects of data science technical projects, including development, deployment, and monitoring.
  2. PhD, Master's, or Bachelor's degree in STEM fields.
  3. High proficiency in at least one programming language, ideally Python, with a strong understanding of object-oriented programming principles.
  4. Understanding of different database technologies, including relational and non-relational databases.
  5. Experience implementing ML automation, MLOps principles, and related tools.
  6. AWS experience is an asset.
  7. Experience with typical DevOps flows, such as containerization and monitoring.
  8. Knowledge of web frameworks and HTTP APIs is desirable.
  9. Understanding of sportsbook products is an asset.
  10. Experience leading and coaching other data scientists.

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