Sports Betting Trading Analyst
AI in this role
Analyze sports betting markets and optimize automated trading strategies using Python and data analysis.
At Longshot Systems we build advanced platforms for sports betting analytics and trading.
We're looking for a Sports Betting Trading Analyst to come and join our modelling team where you will be one of our sports & betting market experts. You'd be joining a small team and working closely alongside software engineers and machine learning experts to provide the domain expert insight in improving the trading strategies we develop for our clients. Your role is to identify trading strategy improvements and value leaks in existing and new strategies through a combination of watching our client's trading activity from our internal tools, data analysis on historical trading and intuition from your sport and betting market knowledge.
You should have a deep interest in sports and sports betting, especially from the professional sports bettor perspective. Ideally you have strong working knowledge of betting exchanges, prediction markets, sharp bookmakers (including the US and Asian markets) and general betting market dynamics. You're a general sports fanatic and enjoy following a wide variety of sports, especially thinking about them from a sports betting angle. You're comfortable with Jupyter notebooks and data analysis in Python. You're numerate and good with numbers, ideally with a degree of core statistical knowledge and understanding.
We are a hybrid working company, working Thursdays in our London (Farringdon) office and flexible the rest of the week. Our typical working hours are 10 am to 6 pm UK time, Monday to Friday, but we support flexible working and trust our team to manage their own schedules to meet their goals. This role especially benefits from working during sporting events, although ultimately it's up to you to decide what's the most valuable use of time and we have excellent tools to re-look at games in normal hours.
Interview Process
- Intro call (30 mins) - your background + interests
- 1st Technical interview (90 mins) - a deeper dive into your experience
- Full assessment day (10:00–6pm) - a one day on-site where you’ll analyse some data we provide for you using Python to generate useful insights.
Responsibilities
- Analyse our existing automated sports betting strategies and identify potential improvements in them
- Collaborate with software developers and machine learning experts to optimise and enhance trading algorithms
- Work with the team to develop brand new trading strategies on new markets and new sports
- Perform data analysis on historical trading to back up your qualitative analysis
- Conduct ongoing research on the sports betting markets
Requirements
Required:
- Strong knowledge of sports betting markets across a variety of different sports
- A strong intuition for spotting bad trading decisions and identifying ways to improve them
- Intermediate to advanced proficiency in data analysis in Python
- Excellent problem-solving skills and ability to work with large datasets
- Strong communication in a predominately remote environment, especially written communication
- Excellent teamwork skills, with the ability to collaborate effectively with software developers and machine learning experts
Desired:
- Previous experience in professional sports betting
- Advanced data science experience
- Experience with quantitative analysis and statistical modelling
- Familiarity with low latency and high throughput trading environments
- An interest in working with the engineers and researchers to implement your improvement ideas directly
Benefits
- Competitive bonus scheme
- 10% matched pension contributions
- Private healthcare insurance
- Long term illness insurance
- Gym membership
How we rate this
Sports Betting Trading Analyst at Longshot Systems rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where sports betting was part of your work. What did you do?
- Tell me about a project where data analysis was part of your work. What did you do?
- Tell me about a project where trading strategies was part of your work. What did you do?
- Tell me about a project where statistics was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Sports Betting, Data Analysis, Trading Strategies, Statistics, and Python. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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