Longshot Systems
Sports Betting Trading Analyst

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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.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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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


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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
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