Quantitative Trader
Pubblicato il 12-09-2026 - Raven in Milano
About Raven
Raven 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.
THE ROLE
Most crypto prediction contracts are digital options in disguise. "BTC above $X at time Y" has a liquid underlying trading right next to it, so fair value is a pricing problem, not a guess, and the risk hedges into spot and perpetuals we already trade with low latency. This cuts both ways. The underlying never stops moving, so a stale quote is easy profit for whoever is faster, and pricing, hedging, and requoting are one problem, not three.
The other half of the book has nothing to hedge against. Protocol upgrades, listings, regulatory decisions, hacks, and governance votes leave you estimating a probability and standing behind it. You will own both, competing against counterparties who are equally skilled.
What You'll Own
Pricing digitals and barriers off the crypto volatility surface. You will work the skew, term structure, and jump risk, and close the gap between a model price and what the market will actually give you
Quoting and market making. Two-sided prices that reprice as the underlying moves, re quote and cancel logic tuned to how fast we can actually reach the venue, and inventory managed across strikes and expiries
Hedging Delta into perpetuals and spot, funding and basis as the cost of carry, and pin risk and gamma as expiry approaches
Event probabilities on the unhedgeable half of the book. Calibrated numbers with explicit priors, sized sm