bet365 Logo

bet365

Data Science Team Leader

Posted 3 Days Ago
Be an Early Applicant
Hybrid
Denver, CO
165K-165K Annually
Senior level
Hybrid
Denver, CO
165K-165K Annually
Senior level
Lead and build a US-based data science capability while remaining hands-on: write code, design, deploy, and maintain production ML models, mentor junior data scientists and ML engineers, establish MLOps and data-science workflows on GCP, and align initiatives with product and global teams to deliver measurable business value.
The summary above was generated by AI
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

This is an exceptional, hands-on, player/coach opportunity to establish, shape, and lead our Data Science capability in the United States. As the Data Science Team Leader, you will be a critical part of our expanding global data organization.

You will remain deeply technical and actively involved in writing code, building models, and executing machine learning solutions, while simultaneously mentoring and growing a high-performing team of US-based Data Scientists and Machine Learning Engineers.

We are intentionally recruiting for a specific kind of professional: someone with a startup mindset who thrives in fast-paced environments, possesses a strong bias for action, and values execution over theoretical complexity. To succeed, you must be a pragmatic problem solver who enjoys getting their hands dirty while building scalable, production-grade solutions.

Excellent stakeholder management is paramount. You will work as a key collaborative partner alongside the US Data Team Lead, Data Product Lead, and AgentOps Team Lead within the wider US Data team, while maintaining strong operational alignment and knowledge sharing with our established UK-based Data Science team.

The listed salary for this position is $165,000 annually.

Qualifications

  • Proven experience working in a fast-paced, agile, or startup-like environment. You must have a demonstrated passion for “getting things done” and delivering value iteratively. 
  • Prior experience mentoring, coaching, or leading data scientists or engineers while remaining active in code development. 
  • A strong track record of designing, building, deploying, and maintaining machine learning models in production environments 
  • Superior communication skills with the ability to build strong cross-functional relationships and translate technical concepts into business outcomes for both technical and non-technical audiences. 
  • Exceptional programming skills in Python and deep expertise in data science libraries (Scikit-learn, Pandas, NumPy, XGBoost, etc.).  
  • Advanced SQL proficiency for querying and manipulating large datasets, preferably within Google BigQuery.  
  • Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem (Pipelines, Workbench, Endpoints). 
  • MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. 
  • Familiarity with containerization (Docker, Kubernetes) and CI/CD principles for machine learning. 
  • Experience with real-time stream processing or event-driven architectures (e.g., Kafka). 

Additional Information

  • In this hands-on role you will devise, code, and deploy AI, machine learning and predictive models, leading by example in technical execution and code quality. This is not a pure people-management role. 
  • Building, mentoring, and guiding a pragmatic, delivery-focused team of Junior Data Scientists and Machine Learning Engineers, fostering a culture of rapid iteration, continuous learning, and software engineering discipline. 
  • Partnering closely with the Data Team Lead, Data Product Lead, and AgentOps Team Lead to align data science initiatives with product roadmaps and platform capabilities. 
  • Collaborating regularly with our UK-based Data Science team of technical excellence to share methodology, align on standards, and leverage global technical capabilities. 
  • Translating complex, ambiguous business questions into clear data science initiatives, delivering measurable business value through rapid prototyping and deployment cycles. 
  • Collaborating with Machine Learning Engineers to champion the adoption of robust MLOps practices on our Google Cloud Platform (GCP) stack, ensuring models are automated, monitored, and scalable. 
  • Establish data science workflows, standards, and code repositories from scratch in a new regional office.

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.

Similar Jobs at bet365

An Hour Ago
In-Office
90K-120K Annually
Senior level
90K-120K Annually
Senior level
Digital Media • Gaming • Software • Esports • Automation
The Senior Windows End User Technology Engineer leads desktop infrastructure management, ensures security compliance, and provides 3rd-line technical support while mentoring team members and optimizing processes.
Top Skills: AutopatchAzureGpoGrafanaIntuneIvantiMicrosoft Endpoint ManagerPatch My PcPowershellSccmSplunkWindowsWsus
2 Days Ago
Hybrid
85K-110K Annually
Mid level
85K-110K Annually
Mid level
Digital Media • Gaming • Software • Esports • Automation
Develop and maintain probabilistic pricing models for real-time sports betting. Analyze large sports datasets, apply machine learning and statistical techniques, optimize model accuracy and computational performance, debug and document code, use source control, and collaborate with traders, data scientists, and developers to productionize pricing algorithms.
Top Skills: C#GoMachine LearningMS OfficePythonRSource Control SystemsSQLWindows
3 Days Ago
In-Office
24-25 Hourly
Entry level
24-25 Hourly
Entry level
Digital Media • Gaming • Software • Esports • Automation
Provide customer support via live chat, phone, and email; investigate and resolve inquiries using internal tools; escalate issues as needed; follow policies, licensing and responsible gambling practices; contribute to process improvements and collaborate with teams.

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account