Quantitative Trading Specialist

White Swan Data

Responsibilities

Trade sporting markets live, pre-match and in-play, taking ownership of pricing, positioning, and risk management in real time.
Set and adjust prices in response to market moves, news, and in-game events, balancing competitiveness against edge.
Turn value signals into executable trading strategies, and refine them based on live performance and market feedback.
Back test and validate strategies before deployment, then operationalise them into automated or semi-automated trading workflows.
Monitor markets and model outputs live, spotting mispricing, adverse selection, and opportunities as they emerge.
Work closely with quants and engineers to translate trading intuition into models, tooling, and process improvements.
Contribute to the acquisition, cleaning, and interpretation of data where it supports pricing and trading decisions.

Experience trading or market-making in betting, gaming, or financial markets (in-play or live trading a strong plus).
Proficiency in an analytical programming language (Python, R or similar).
Proficiency in production ready engineering (Architecture, low latency systems, Java or C++)
BSc in mathematics, statistics, computer science, engineering, or another quantitative discipline.

Strong trading instinct and comfort making pricing and risk decisions under time pressure and uncertainty.
Knowledge of sports rules, player dynamics, and team strategies, plus a solid grasp of how its betting markets behave.
Sound quantitative and statistical foundation, enough to interrogate models, understand their assumptions, and know when to trust or override them.
Strong attention to detail and the ability to retain and act on information quickly.
Strong communication and collaboration skills.
Positive 'can do' attitude and the ability to meet deadlines.
Willingness to learn and adapt to new environments.