About the job
Longshot Systems builds advanced platforms for sports betting analytics and trading. The team blends software engineering, machine learning, and expertise in sports markets to develop trading strategies for clients.
Role overview
The Sports Betting Trading Analyst joins the modeling team as a subject matter expert in sports and betting markets. This role works closely with software engineers and machine learning specialists to refine and improve trading strategies. Key responsibilities include monitoring client trading activity, analyzing historical trade data, and applying deep knowledge of the sports betting landscape to spot improvements and value leaks in both current and new strategies.
What you will do
- Work with engineers and machine learning specialists to enhance trading strategies
- Analyze historical trades and client activity to identify areas for improvement
- Apply expertise in sports and betting markets to find value opportunities and leaks
- Use data analysis tools, especially Python and Jupyter notebooks, to extract insights
- Engage with a wide range of sports from a betting perspective
Requirements
- Strong passion for sports and sports betting, ideally with experience as a professional bettor
- Deep understanding of betting exchanges, prediction markets, and sharp bookmakers, including US and Asian markets
- Proficiency with Jupyter notebooks and data analysis in Python
- Strong numerical skills and a solid background in statistics
- Interest in following a broad range of sports, especially through the lens of betting
Working arrangements
This position follows a hybrid working model. Thursdays require in-person attendance at the London (Farringdon) office, while the rest of the week offers flexibility. Core hours are 10 am to 6 pm UK time, Monday through Friday, with support for flexible working to help the team meet goals. The role often benefits from engagement during sporting events, and tools are available to review games outside regular hours.
Interview process
- Introductory call (30 minutes) to discuss background and interests
- First technical interview (90 minutes) for an in-depth discussion of experience
- Comprehensive assessment day (10:00 am - 6:00 pm) on-site, focused on data analysis using Python to generate insights

