Senior Data Scientist - Trading

Location: Denver, Colorado, us

Company Description

At bet365, 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 9,000 people and serve over 100 million customers in 27 languages. Our focus on In-Play betting has solidified our market-leading position, offering an unmatched experience across 96 sports and 700,000 streaming events. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe, we handle over 6 billion HTTP requests daily and process more than 2 million bets per hour at peak.

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 opportunities for growth, 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 customers worldwide.

Job Description

We are building a next-generation trading platform at bet365, driving high-performance automation and real-time intelligence at scale. As a Senior Data Scientist in our Trading Intelligence team, you will embed machine learning into operations to deliver measurable business impact.

In this key technical leadership position, you will guide high-impact modeling, champion fast, safe iterations on our modern cloud stack, and mentor emerging talent to grow the team's data science capabilities - establishing the standard for methods, delivery, and communication.

Embedded directly within Trading, you will collaborate closely with stakeholders and central engineering teams to frame problems, prototype models, and deploy solutions rapidly. Your work will balance statistical rigor with commercial impact, delivering tangible results while maintaining oversight of cloud experiment costs.

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

Qualifications

• PhD or MSc in a quantitative field (Computer Science, Statistics, Engineering) or equivalent industry experience.
• Demonstrable experience in data science with a track record of deploying and maintaining machine learning systems in production.
• Strong programming skills in Python and expertise in data science libraries (e.g., Scikit-learn, Pandas, NumPy, XGBoost); advanced proficiency in SQL.
• Extensive hands-on experience with Google Cloud Platform (GCP) and Vertex AI, including building and automating ML workflows.
• Experience with iGaming or online sports betting operators is a strong plus.
• A pragmatic, value-oriented mindset with strong communication skills, capable of translating complex technical concepts for diverse audiences.

Additional Information

• Drive end-to-end data-driven trading solutions, from problem framing to model deployment.
• Champion practical MLOps on GCP, defining data, feature, deployment, and monitoring requirements.
• Collaborate with the central data science and engineering team for pipeline support and monitoring.
• Deliver business value quickly by translating complex needs into tangible data science applications.
• Maintain cloud cost awareness and ensure visibility of experiment and application costs.
• Automate and scale frameworks for model testing, validation, and monitoring.
• Experiment and optimize to measure real-world impact, balancing statistical rigor with practical decision-making.
• Build the next generation of data-driven intelligence into core trading processes.
• Mentor and coach emerging team members to grow local data science capabilities, ensuring robust methods and effective communication.

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.