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.
Join our US Data team. We want curious minds who love fast execution and real impact. Kickstart your career in an environment that values practical results over theoretical perfection.
You will work on real-world business challenges, learning from senior colleagues, and deploying machine learning solutions directly to production.
We want a candidate with a “startup attitude”—someone who is energetic, eager to learn, and possesses a strong “get it done” personality. You are not afraid to ask questions, experiment rapidly, and iterate on solutions.
Reporting directly to the Data Science Team Leader, you will collaborate with Machine Learning Engineers and Data Scientists both in the US and the UK. You will gain extensive hands-on experience across our cutting-edge, cloud-native Google Cloud Platform (GCP) and MLOps tech stack.
The listed salary for this position is $70,000-$85,000 annually.
bet365 provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.