What the candidate will do
- Own the research agenda: identify bottlenecks, prioritize and justify hypotheses
- Analyze transaction costs and market impact: slippage, spreads, time decay
- Design risk frameworks when introducing new trading approaches
- Run backtests, evaluate results honestly, monitor live behavior
- Build trading modules to test hypotheses
- Make architectural decisions on the research pipeline, set tasks for the production team
Must-have
- Personal experience managing trading capital at risk (main filter — see below)
- ~3 years at a firm managing capital at risk (tenure can be shorter if the quality is there — 1 year of real book ownership beats 10 years of data science)
- Strong foundation: statistics, probability theory, numerical methods (optimization, interpolation, ODEs)
- Experience in arbitrage trading or trading analysis + understanding of market microstructure
- Confident Python + SQL (ClickHouse); C++ or C# / Java — at least one at a real production level
- Ability to independently formulate testable hypotheses and honestly evaluate results
- English — confident written; spoken is a plus
Nice-to-have
- Options: Greeks, skew, volatility (valuable but not a blocker — add to screening questions)
- ML / neural nets in a trading context
- Background in applied math, physics, or finance; competitive olympiad background (Mekh-Mat, Phystech, HSE FCS)
We are partnering with Fintech Company on a specialist search for a senior engineer. The role is based in Moscow, Russia and offered as onsite contract work. Compensation is Competitive.
Apply today.