What are the responsibilities and job description for the Quantitative Trader position at Albert Bow?
Quant Trader – Prediction Markets
We’re partnering with a fast growing prediction markets trading firm looking to hire a Quant Trader to help build and scale systematic trading strategies across Kalshi & Polymarket.
The team operates at the intersection of trading, quantitative research, and real world event forecasting, with a strong focus on pricing inefficiencies, liquidity dynamics, and automated execution across prediction market venues
Responsibilities
• Develop and deploy systematic trading strategies across prediction markets and event driven products
• Research pricing inefficiencies across sports, politics, macro, crypto, and real world event markets
• Build quantitative models around probabilities, market behaviour, and order flow dynamics
• Analyse exchange microstructure, liquidity, and execution performance across venues
• Design and optimise automated execution and market making systems
• Monitor live trading performance, risk exposure, and strategy health in production
• Work closely with engineering and data teams to improve infrastructure and scalability
• Identify new datasets and alternative signals to improve forecasting and pricing accuracy
Desired Skills
• Strong experience in quantitative trading, sports trading, market making, or systematic research
• Excellent Python skills, experience with C , Rust, or low latency systems is beneficial
• Understanding of exchange based trading environments and execution dynamics
• Interest in prediction markets, event driven trading, sports modelling, or behavioural inefficiencies
• Ability to operate independently within fast moving, high ownership environments
• Strong academic background in Mathematics, Physics, Computer Science, Engineering, or a related quantitative field
Experience across prediction markets, sports betting, crypto derivatives, HFT, market making, or statistical arbitrage is highly relevant.
Salary : $150,000 - $275,000