Quantitative Trader - Sports Prediction Markets
Pubblicato il 30-10-2026 - Raven in Milano
ph3About Raven /h3 pRaven is a proprietary crypto market-making and high-frequency trading firm. We trade spot, perpetuals, and prediction markets with dedicated low-latency infrastructure across eight major trading regions. /p h3About Raven /h3 pRaven is a proprietary crypto market-making and high-frequency trading firm. We trade spot, perpetuals, and prediction markets with dedicated low-latency infrastructure across eight major trading regions. We hire competitive individuals and natural problem solvers with a record of ranking at something hard, whether competitive programming, games, or mathematics, who treat an unfamiliar problem as a challenge rather than an obstacle. We can teach markets; we cannot teach drive. We build our own stack end to end, from connectivity and pricing through execution, monitoring, and research data. /p h3THE ROLE /h3 pWe are not a sportsbook. We do not price a margin and wait for retail flow. We quote into exchange-style markets where the counterparty may be sharper than we are, and we profitonly when our probabilities beat the price.This is the whole job. Every contract settles at zero or one, the market price is already a forecast, and your edge is being better calibrated, faster to react, or willing to make a market where no one else will. /p h3What You'll Own /h3 ul liEvent models. Team and player state turned into a probability distribution, built from ratings, lineups, pace, venue and weather effects, and referee quirks. A stable of models rather than one grand unified theory, and you know exactly where each one stops working /li liQuoting and market making. Two-sided prices on discrete outcomes, with spread and size that reflect how confident the model actually is, and inventory managed across outcomes that must sum to one /li liNews, latency, and in-play. Injuries, lineups, red cards, and delayed starts,
met with state-dependent live repricing and suspension logic that withdraws quotes before adverse selection sets in /li liResolution risk. What a contract actually settles on, in the rules text and not the spirit. Real PnL, not legal boilerplate /li liRisk and sizing. Position sizing that survives a bad week, correlation across events that look independent and are not, and exposure you understand before it is a problem /li /ul h3Who We're Looking For /h3 ul liDemonstrated skill forecasting real-world events for money, supported by quantitative evidence, from a betting syndicate, professional or semi-professional betting, a research seat graded on calibration, or sportsbook trading if you can demonstrate the transition described below /li liYou think in probabilities and know when you are wrong. You can explain how you would validate a model, what would count as evidence against it, and which of your own models you have retired /li liStrong applied statistics, including Bayesian inference, hierarchical models, time-varying team strength, and enough machine learning to know when it is the wrong tool /li liData instincts. Odds histories, lineups, injuries, and results are messy and revised after the fact, and you catch the look-ahead bias before it flatters a backtest /li liIf you are from a sportsbook, the transition that matters is from pricing recreational flow to competing against a market. We look for evidence you can tell the difference /li liFluent English /li liCrypto and exchange microstructure are a plus /li liNo degree required. Experience is what matters /li /ul h3LOGISTICS /h3 ul liSofia (Bulgaria) or Milan (Italy), with no preference between them. Whichever city the right person is in /li liIn office, not remote /li liCrypto trades around the clock. You will share a sane on-call rotation with the team that owns these systems /li /ul /p #J-18808-Ljbffr