At a Glance
- Tasks: Develop and deploy advanced predictive systems using deep learning and statistical models.
- Company: Join a dynamic team at Mettle Data, focused on innovation in sports betting.
- Benefits: Fully remote work, competitive salary, and opportunities for career progression.
- Other info: Be part of a small, ambitious team with a profitable model already in production.
- Why this job: Make an impact in the exciting world of sports data with cutting-edge technology.
- Qualifications: Strong Python and SQL skills, plus experience with machine learning and messy datasets.
The predicted salary is between 60000 - 80000 £ per year.
We are hiring a Quant / Data Scientist to build the model layer behind Mettle Data. This role is focused on developing and deploying advanced predictive systems across sports and market data, with a particular emphasis on deep learning approaches alongside traditional statistical models.
You will work on end-to-end model development: feature generation from noisy, high-frequency data, training and tuning deep learning architectures, backtesting, calibration, live-versus-backtest diagnosis, and production monitoring. A core part of the role is improving the live evidence loop and determining which modeling approaches (including neural network-based pipelines) should be advanced into production.
We already operate a profitable model in production; the next phase is pushing model sophistication while maintaining rigorous validation and real-world performance discipline. We are looking for strong Python and SQL skills, deep understanding of machine learning and modern deep learning techniques, and a high bar for empirical validation. Experience working with real-world, messy datasets is essential. Backgrounds in sports, quantitative finance, or trading systems are a strong plus.
This is an opportunity to join a small, highly-skilled and ambitious team, with significant opportunity for progression. This role is fully-remote.
Sports Betting Quant / Data Scientist employer: Mettle Data
Join a dynamic and innovative team as a Sports Betting Quant / Data Scientist, where you will have the opportunity to work on cutting-edge predictive systems in a fully-remote environment. Our company fosters a collaborative work culture that values creativity and encourages professional growth, offering ample opportunities for career advancement while working with advanced technologies in sports and market data. With a focus on rigorous validation and real-world performance, you will be part of a passionate team dedicated to pushing the boundaries of model sophistication.
StudySmarter Expert Advice🤫
We think this is how you could land Sports Betting Quant / Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the sports betting and data science communities. Attend webinars, join forums, or hit up LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving predictive models or deep learning. Share your work on GitHub or personal blogs to demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss your experience with messy datasets and how you've tackled challenges in model development. Practice explaining complex concepts in simple terms – it’ll impress the interviewers!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our ambitious team at StudySmarter.
We think you need these skills to ace Sports Betting Quant / Data Scientist
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python and SQL skills in your application. We want to see how you’ve used these tools in real-world scenarios, especially with messy datasets. Don’t hold back on showcasing your experience with machine learning and deep learning techniques!
Tailor Your Application:Take a moment to customise your application for this role. Mention specific projects or experiences that relate to sports betting or quantitative finance. We love seeing how your background aligns with what we’re doing at Mettle Data!
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications and experiences. Avoid fluff – we want to know what makes you a great fit!
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 our team and culture!
How to prepare for a job interview at Mettle Data
✨Know Your Models
Make sure you’re well-versed in both traditional statistical models and deep learning techniques. Be ready to discuss specific models you've worked with, how you approached feature generation from messy datasets, and the results you achieved. This shows your depth of knowledge and practical experience.
✨Showcase Your Python and SQL Skills
Prepare to demonstrate your coding skills during the interview. You might be asked to solve a problem on the spot or explain your thought process behind a project. Brush up on your Python libraries for data science and SQL queries, as these are crucial for the role.
✨Discuss Real-World Applications
Be ready to talk about how you've applied your skills in real-world scenarios, especially in sports or quantitative finance. Share examples of how you’ve improved model performance through rigorous validation and backtesting, as this will resonate with the team’s goals.
✨Emphasise Team Collaboration
Since this is a small, ambitious team, highlight your ability to work collaboratively. Discuss any past experiences where you contributed to a team project, particularly in a remote setting. This will show that you can thrive in their work environment and contribute positively to the team dynamic.
