Senior Quant Researcher (Prop / Systematic trading)

We are a prop-trading firm that blends the agility of a startup with the capabilities of a high-performing fund. We build advanced, data-driven trading strategies across asset classes, and foster a culture where ideas matter, ownership is encouraged, and every team member can unlock their full potential.

This role is for a Senior quant who wants to own the full lifecycle of a strategy: generate ideas, research and validate them properly, deploy to production, and run the strategy with robust risk control.

We can provide a strategy direction / starting thesis and the data/infra — you take it to a live, trading system.

We care about good decisions and robust strategies, not about specific models or fashionable architectures.ML is a tool, not a goal.

What You Will Do

• Formulate and test investment hypotheses; turn them into live systematic strategies
• Build the full pipeline: data, signals/features, model, execution, risk, monitoring
• Design validation for markets: non-IID data, regime shifts, leakage control, walk-forward
• Own risk: position sizing, limits, stress tests, scenario analysis, tail-risk awareness
• Model real trading constraints: transaction costs, slippage, market impact, and capacity
• Run post-trade analytics: PnL attribution, drawdown analysis, signal decay, and model drift
• Partner with research/engineering/execution to make sure strategies actually trade
  
  

What success looks like

• You can take a thesis from "idea" to a live strategy with solid validation and risk controls
• You can explain what drives PnL, when it breaks, and how you detect/mitigate drift
• You raise the bar for research rigor and production readiness
  
  

Requirements

• 5+ years in quantitative research, systematic trading, or ML-driven modeling for markets
• Proven production deployment of strategies/models with measurable outcomes (live trading or equivalent)
• Strong stats + time-series fundamentals (non-stationarity, dependence, tails, robustness)
• Strong Python and engineering discipline (reproducible research, clean code, tests/monitoring mindset)
• PM-style thinking: returns vs risk vs costs, not "models for models"
• English and Russian are both working languages, and we are particularly open to Russian-speaking quants with international backgrounds. We work in an international, multilingual team.
  
  

Nice to have

Experience trading options/volatility, strong ML for time series, or a deep applied math/physics/econophysics background is a major plus.

Tech (what You'll Use)

• Python; PyTorch if ML-heavy
• Docker; experiment/research reproducibility tools (DVC/MLflow—tooling not strict)
• Large, multi-source datasets (market + macro + alternative data)
  
  

You are not expected to be an expert in every area.We value ownership, depth, and good judgment over trying to cover everything at once.

Benefits

• Culture of innovation — a genuinely open, research-driven environment where curiosity is rewarded and your ideas directly shape real trading strategies
• True flexibility — work from anywhere; we care about outcomes, not where or when you sit at your desk
• High autonomy & ownership — no micromanagement, no bureaucracy. You get full responsibility over your research direction, models, and production impact
• Startup agility, Fund resources — fast decision-making, minimal red tape, and access to the data, compute, and infrastructure you need to run serious research
• Massive data advantage — work with a uniquely rich multi-modal dataset (order log, options chains, satellite data, alt-data, Bloomberg, proprietary feeds)
• Top-tier equipment — choose the hardware/software setup that makes you most productive
• Well-being support — 35 days of vacation, 100% paid sick leave, and access to a corporate psychologist
• Real career growth — shape research culture, lead initiatives, and influence long-term strategy directions