Data Scientist (CricViz)

CricViz is looking for a Data Scientist to join us at the cutting edge of sports analytics.  This role is remote with some travel to London required for team meetings.  The role is starting ASAP.  Salary competitive – depending on experience.

About the role:

  • You will be using the world’s largest cricket database and working with leading cricket analysts to further develop our understanding of the game.
  • You will be analysing granular tracking data to generate new insights on player and team performances.
  • You will be working within a team to develop new metrics for use by clients such as broadcasters and professional coaches/teams.
  • You will be building accurate pricing models for new betting markets.
  • You will have full autonomy on ideas and approaches to projects.
  • You may also have the opportunity to work on other sports in the business.
    and Rugby

Requirements:

  • Knowledge of machine learning and statistical methods, e.g. linear/logistic regression, decision trees, random forest, unsupervised methods, neural networks etc.
  • Experience with the PyData stack (e.g. pandas, numpy, scikit-learn, XGBoost, matplotlib).
  • Experience using databases and SQL.
  • Knowledge and thorough understanding of sports betting markets.
  • A passion for data & ability to convey complex information through Data Visualisation.
  • Ability to manage different responsibilities and adapt to changing business needs.
  • Strong interest and knowledge in a variety of sports – in particular cricket.

Benefits:

  • 25 days holiday
  • Flexible working times
  • Company pension scheme
  • Access to matches at The Oval, London

To apply, please send your CV to careers@cricviz.com with the subject “CricViz Data Scientist Vacancy”.  Please also include an example of work demonstrating the above skills (e.g. blog post or GitHub repo) and/or a covering note outlining your relevant experience.

The deadline for applications is 25th May 2022.

We cannot promise to respond to all applicants due to the volume we receive.