Quant Trader

Quant Trader (Prediction Markets) — Remote Europe A fully remote trading company operating in prediction markets is looking for a Quantitative Trader to join a senior team building high-performance automated trading systems. The business is backed by an established tier 1 iGaming and sports betting operator and benefits from significant industry expertise, technology, and resources. The role is focused on overseeing highly automated live trading, improving trading strategies, identifying and validating edge, and safely rolling improvements into production. Performance will be measured through areas such as EV gains, fill quality, and trading-system uptime. This is a live-markets position. It is not a traditional 9-to-5 role, and some weekend coverage is expected as part of the trading team's shared schedule. Main Responsibilities: Monitor live automated trading, including performance, exposure, market behaviour, and risk during sporting events. Adjust algorithmic trading behaviour when required and intervene through hedging or halting when markets, models, or data behave unexpectedly. Research, test, and improve pricing, signals, quoting strategies, models, and risk logic across sports prediction markets. Manage the safe rollout of strategy changes using shadow, canary, or staged-exposure approaches. Analyse trading data including P&L attribution, fill quality, slippage, exposure, and model performance. Backtest and simulate strategy changes before they are introduced into live markets. Work closely with trading-systems engineers to translate strategy ideas into production logic and improve trading tools, controls, and guardrails. Contribute trader judgement to product decisions around instrument design, pricing, settlement, and risk. Desired experience: Strong sports betting domain knowledge is essential. Experience within a sportsbook, betting exchange, betting operator, financial trading environment, or a demonstrable personal betting track record. Good understanding of probability, statistics, expected value, edge, risk, and market dynamics. Comfortable analysing trading data using Python and/or SQL. Experience using AI tools to support research, analysis, and reporting. Python skills are sufficient for the role. C#/.NET knowledge is advantageous but not mandatory. Quantitative background through Mathematics, Computer Science, Engineering, Statistics, Economics, or equivalent practical experience. Willingness and genuine interest in working around US sporting events, including some weekends. Comfortable working with ownership and ambiguity in an early-stage environment. Experience with prediction markets, exchange-style products, sports modelling, machine learning, automated trading strategies, BI/reporting, or C#/.NET would be advantageous but is not 100% mandatory.