Senior Data Scientist

We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000.

Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages.

We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity.

This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling.

As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our global worldwide.

Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year.

With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak.

As a Senior Data Scientist, you will accelerate our end-to-end machine learning lifecycle, building on our strong data science foundation to scale impact and automate business decisions.

The data science team is at the forefront of driving business decisions, we are now scaling our impact with a focus on automation and advanced MLOps practices on Google Cloud.

This is a key technical leadership role where you will champion rapid iteration and innovation, this will be instrumental in elevating our ability to deliver measurable value.

You will be responsible for the end-to-end lifecycle of machine learning solutions that optimize our Sports and Gaming products, from development to automated deployment and monitoring.

This is an exciting opportunity to apply cutting-edge data science and MLOps principles in a fast-paced, high-impact environment, tackling complex challenges in areas like Trading, Fraud, Responsible Gaming, and Personalization.

The listed salary for this position is $135,000 – $150,000 annually.

• PhD or MSc in a quantitative field such as Computer Science, Statistics, or Engineering, or equivalent industry experience delivering complex data science projects.
• Demonstrable experience deploying and maintaining machine learning systems in a production environment with measurable business impact.
• Strong programming skills in Python and deep expertise in data science libraries such as, Scikit-learn, Pandas, NumPy, XGBoost.