Sports Betting Quantitative Researcher

ABL Recruitment; Greater London; Hybrid; GBP 66,000 - 110,000; Full time

Benefits offered by this job

Profit-share bonus

Job summary

ABL Recruitment is assisting a high-performance quantitative sports trading business in London to hire a Sports Betting Quantitative Researcher. You will build predictive models and trading strategies across sports markets, moving from research and backtesting into live trading with real-time results.

Ideal candidates have 3+ years of experience in sports betting modelling, strong Python skills, and hands-on ML with TensorFlow or PyTorch. In-play betting and rating systems knowledge is a plus.

Qualifications

• 3+ years’ experience building predictive models in sports betting or related field.
• Proven track record of models used to price or trade sports markets.
• Strong Python skills with NumPy, pandas, SciPy, scikit-learn.
• Hands-on ML with TensorFlow/Keras or PyTorch.
• Understanding of probability, stats, calibration.
• Knowledge of Kelly criterion, bankroll management, stake sizing.
• Experience in tennis, football, NBA or UFC modelling.
• Experience in in-play or exchange betting.
• Experience with Elo/Glicko/TrueSkill.
• Model deployment from research to production.
• Git, cloud infra, model versioning, and automated retraining.

Responsibilities

• Build and improve predictive models for sports betting markets.
• Develop features from historical data, Elo/rating, odds.
• Develop probability models and calibration techniques.
• Build trading signals and position sizing methodologies.
• Backtest models with realistic historical data.
• Address overfitting and data leakage.
• Analyze live and post-trade performance to identify edge.
• Take ownership of models from research to production.
• Present research findings to the CIO and trading team.

Skills

Python

ML

Statistics

Backtesting

Communication

NumPy/Pandas

SQL

Git

TensorFlow/Keras

PyTorch

Education

Bachelor's degree in Mathematics/Statistics/CS

Master's or PhD advantageous

Tools

TensorFlow/Keras

PyTorch

SQL

Git

Cloud infrastructure

Job description

An exciting opportunity to join a high-performance quantitative trading business developing predictive models and systematic strategies across sports betting markets.

· Job title: Sports Betting Quantitative Researcher

· Location: Central London / Hybrid

· Job Type: Full-time, Permanent

· Salary: up to £110K + profit-share bonus

The Opportunity

We are recruiting on behalf of a high-performance quantitative sports trading business looking for a Sports Betting Quantitative Researcher with proven experience building predictive models within sports betting.

You’ll develop and improve models and trading strategies across sports markets, working closely with experienced researchers, engineers, traders and the CIO. This is an end-to-end role where your models can move from research and backtesting into live trading.

Key Responsibilities

• Build and improve predictive models for sports betting markets using TensorFlow/Keras, PyTorch or similar.
• Develop features from historical match data, player performance, Elo/rating systems, market odds and other sports data.
• Develop probability models and calibration techniques to improve predictive accuracy and market edge.
• Build trading signals, strategy parameters and position-sizing methodologies.
• Backtest models and strategies using realistic historical market prices, liquidity and time-aware validation.
• Identify and address overfitting, data leakage and look-ahead bias.
• Analyse live and post-trade performance to identify and improve sources of edge.
• Take ownership of models from initial research through to production and live trading.
• Present research, results and recommendations clearly to the CIO and trading team.

About You

• 3+ years' experience building predictive models specifically within sports betting, sports trading or a closely related quantitative sports environment.
• Proven experience developing models that have been used to price or trade sports markets.
• Strong Python skills, including NumPy, pandas, SciPy and scikit-learn, plus solid SQL.
• Hands-on experience with machine learning and neural networks using TensorFlow/Keras or PyTorch.
• Strong understanding of probability, statistical modelling and model calibration.
• Practical understanding of betting markets, odds, overround, liquidity and closing line value.
• Knowledge of Kelly criterion, bankroll management and quantitative stake sizing.
• Strong research discipline, including walk-forward validation, avoiding leakage and controlling overfitting.
• Degree in Mathematics, Statistics, Physics, Computer Science or another quantitative discipline.
• Master's or PhD is advantageous but not essential.
• Strong communication skills and the ability to explain modelling decisions and research findings clearly.
• Experience modelling tennis, football, NBA or UFC.
• Experience with in-play or exchange betting.
• Experience with Elo, Glicko, TrueSkill or similar rating systems.
• Experience taking models from research into live production.
• Experience with Git, cloud infrastructure, model versioning and automated retraining.
• Demonstrable live betting results, model performance or published research.

Why This Role?

This is an opportunity for a sports betting quant to move beyond pure research and take genuine ownership of models that are deployed into live markets.

You’ll have direct access to senior decision-makers, see the performance of your models in real time and receive a profit-share bonus linked to the strategies you build and contribute to.