Quantitative Trader - Sports Prediction Markets

Posted 2 Days Ago
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3 Locations
In-Office or Remote
Entry level
Financial Services • Cryptocurrency
The Role
Build and operate probability-based sports event models for prediction markets, quote two-sided prices, manage inventory and risk, and reprice markets in response to news and live events. The role requires strong applied statistics, Bayesian modeling, calibration, data quality controls, and real-money forecasting experience. Work is conducted in-office in Sofia or Milan with participation in an on-call rotation supporting around-the-clock crypto trading systems.
Summary Generated by Built In
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

We 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 profit only 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.

WHAT YOU'LL OWN

- Event 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

- Quoting 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

- News, 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

- Resolution risk. What a contract actually settles on, in the rules text and not the spirit. Real PnL, not legal boilerplate

- Risk 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

WHO WE'RE LOOKING FOR

- Demonstrated 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

- You 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

- Strong applied statistics, including Bayesian inference, hierarchical models,  time-varying team strength, and enough machine learning to know when it is the wrong tool

- Data 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

- If 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

- Fluent English

- Crypto and exchange microstructure are a plus

- No degree required. Experience is what matters

LOGISTICS

- Sofia (Bulgaria) or Milan (Italy), with no preference between them. Whichever city the right person is in 
- In office, not remote
- Crypto trades around the clock. You will share a sane on-call rotation with the team that owns these systems

Skills Required

  • Demonstrated skill forecasting real-world events for money, supported by quantitative evidence
  • Strong probability and statistical reasoning, including model validation and calibration
  • Applied statistics knowledge, including Bayesian inference, hierarchical models, and time-varying team strength
  • Ability to identify data quality issues and prevent look-ahead bias in backtesting
  • Fluent English
  • Willingness to work in-office in Sofia, Bulgaria, or Milan, Italy
  • Availability to participate in an on-call rotation for around-the-clock crypto trading systems
  • Crypto and exchange microstructure knowledge
  • Machine learning knowledge sufficient to determine when it is appropriate or inappropriate
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The Company
16 Employees
Year Founded: 2023

What We Do

Raven is a proprietary algorithmic high-frequency trading firm and institutional market maker providing liquidity across cryptocurrency spot and perpetual markets, centralized and decentralized exchanges, prediction markets, and select traditional financial venues. It uses low-latency, high-throughput infrastructure to quote across these markets. Raven says its work is intended to improve market stability and efficiency, while building long-term partnerships with exchanges and projects.

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