Data Scientist

Kindred Group

London, United Kingdom

The role

We are building the sportsbook of tomorrow at Kindred. Machine learning algorithms and AI are at the heart of how we will deliver an unrivalled customer experience and unlock operational efficiencies through automation.

Our Data Science (DS) and Machine Learning Engineering (MLE) teams are currently focused on delivering Personalisation and Risk Management products, with future scope to develop sportsbook specific Reward products, and collaborate with our Quant team to develop trading automation solutions.

We are recruiting a Data Scientist to join our product-led team and contribute to the success of our Kindred Sportsbook Platform. This role will report into our Risk Management team.

What you will do

Actively contribute to product development, able to interpret requirements and deliver independently.
Work closely with business stakeholders to translate business requirements into data science use cases, proactively reaching out in ambiguous situations, adapting to feedback and generating insights/solutions backed by data to drive the decisions.
Collaborate with DS and MLE team members to build and deliver data-driven products.
Take technical ownership of models throughout their lifecycle.
Write code that follows best practices and facilitates collaboration and re-usability.

Your experience

Bachelor's or advanced degree in a STEM subject.
Experience in a DS role with a proven track record successfully delivering algorithmic data products for enterprise-grade solutions in collaboration with engineering teams.
Proactively solving problems and proposing new solutions where existing methodology may not exist.
Accountability for the decisions taken within the projects and ability to clearly explain the reasoning
Interest and understanding of sports betting, experience in sports risk management.
Excellent interpersonal skills, able to explain complex concepts to stakeholders.
Strong knowledge of machine learning algorithms and general statistical methodologies and theory.
Basic knowledge of AB testing and design of experiment.
Advanced Python and SQL skills, experience using Spark for processing large datasets.
Understanding of software product development processes and governance, including CI/CD processes and release and change management.
Familiarity with cloud computing platforms, ideally experience with Amazon Web Services.