At a Glance
- Tasks: Lead the design and deployment of machine learning models for sports betting predictions.
- Company: Join a cutting-edge sports analytics company with a remote-first culture.
- Benefits: Generous compensation, flexible remote work, and opportunities for professional growth.
- Why this job: Make an impact in the exciting world of sports betting with innovative ML solutions.
- Qualifications: 5+ years in data science, leadership experience, and expertise in sports betting models.
- Other info: Collaborative environment with a focus on continuous learning and development.
The predicted salary is between 54000 - 84000 £ per year.
About the Role
We are looking for a Lead Data Scientist to head our machine learning model development operation. You will design, build, and deploy predictive models that estimate sports outcome probabilities, models that directly drive our betting strategy on prediction markets. This is a hands-on leadership role. You will own the full model lifecycle from research through production, lead a team of data scientists, and continuously improve our predictive edge. The role will be fully remote with a generous compensation package; previous experience with building sports betting models is essential.
Responsibilities
- Lead the design, development, and deployment of machine learning models for sports outcome prediction
- Manage and mentor a team of data scientists and data engineers
- Build and validate deep learning architectures (CNNs, Transformers, neural networks) for structured sports data
- Develop back testing frameworks and rigorously validate model performance against historical data
- Collaborate with trading and engineering teams to integrate models into live betting operations
- Ensure data quality, pipeline integrity, and model monitoring in production
- Stay current with advances in sports analytics, ML research, and betting market dynamics
Requirements
- 5+ years of experience as a Data Scientist or ML Engineer, with at least 2 years in a leadership role
- Proven experience building sports betting or prediction models - this is essential
- Strong expertise in deep learning frameworks (PyTorch, TensorFlow) and techniques (neural networks, CNNs, Transformers)
- Advanced proficiency in Python and SQL
- Solid foundation in statistics, probability theory, and predictive modelling
- Experience deploying ML models to production environments
- Excellent communication skills - ability to translate complex findings for non-technical stakeholders
- Degree in Computer Science, Data Science, Statistics, Mathematics, Physics, or related quantitative field
Lead Data Scientist- Sports Betting ML in Oxford employer: SIRE
Contact Detail:
SIRE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist- Sports Betting ML in Oxford
✨Tip Number 1
Network like a pro! Reach out to your connections in the sports betting and data science fields. Attend relevant meetups or webinars, and don’t be shy about asking for introductions. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous work with predictive models, especially those related to sports betting. We recommend using platforms like GitHub to share your projects. This way, potential employers can see your expertise in action.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you’ll need to communicate effectively with non-technical stakeholders. We suggest doing mock interviews with friends or using online resources.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged. So, get your application in and let’s make some magic happen!
We think you need these skills to ace Lead Data Scientist- Sports Betting ML in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with sports betting models and any leadership roles you've held. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific projects where you've designed, built, or deployed machine learning models. If you've worked with deep learning frameworks like PyTorch or TensorFlow, let us know! We love seeing real-world applications of your skills.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're passionate about sports analytics and how your experience makes you the perfect fit for our team. Keep it engaging and personal – we want to get to know you!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about StudySmarter and what we do!
How to prepare for a job interview at SIRE
✨Know Your Models Inside Out
Make sure you can discuss your experience with building sports betting models in detail. Be prepared to explain the methodologies you used, the challenges you faced, and how you overcame them. This will show your depth of knowledge and hands-on experience.
✨Showcase Your Leadership Skills
Since this role involves leading a team, be ready to share examples of how you've managed and mentored data scientists or engineers in the past. Highlight specific instances where your leadership made a difference in project outcomes or team dynamics.
✨Brush Up on Technical Skills
Familiarise yourself with the latest deep learning frameworks like PyTorch and TensorFlow. Be prepared to discuss your proficiency in Python and SQL, and maybe even solve a coding challenge during the interview to demonstrate your skills.
✨Stay Current with Industry Trends
Research recent advancements in sports analytics and machine learning. Being able to discuss current trends and how they might impact the betting market will show that you're not just knowledgeable but also passionate about the field.
