Quantitative Researcher

We are the creators of a new fintech era!

Our mission is to revolutionize the world by making blockchain technology accessible to everyone in everyday life. WhiteBIT is a global team of more than 1,500 professionals united by a shared vision of shaping the future.

We are building our own blockchain ecosystem to ensure maximum transparency and security for over 8 million users worldwide. Our cutting-edge solutions, rapid adaptation to market challenges, and technological excellence set us apart from traditional companies.

Our official partners include Juventus, FC Barcelona, Lifecell, FACEIT, and VISA.

Join us as an Quantitative Researcher.

• MSc or PhD in a quantitative field; a live trading track record outweighs credentials
• 5+ years in quantitative research or trading at a top-tier HFT firm, market maker, systematic fund, or crypto-native market maker; exchange-side market-structure experience is a plus
• Hands‑on experience with at least one Trad Fi asset class (FX, futures, equities) and / or equivalent crypto asset classes; both maker and taker strategies

• Advanced probability, statistics, time‑series analysis, optimization; strict validation discipline (multiple testing, out-of-sample hygiene, live–sim parity)
• Market microstructure: order‑book dynamics, queue position, fill probability, adverse selection and markouts, market impact
• Expert Python (Num Py, pandas/Polars, PyTorch); working C++ or Rust for latency‑critical components
• Tick‑data engineering at scale: columnar stores, cross‑venue normalization, data‑quality control

• Crypto microstructure: CEX matching engines and fee schedules, perpetuals (funding, mark price, liquidation/ADL), cross‑venue arbitrage, DEX/AMM basics
• Trad Fi microstructure: FX ECN mechanics (firm vs last‑look liquidity, prime brokerage), listed futures; low‑latency architecture (tick‑to‑trade path, colocation, exchange protocols)
• Inventory and hedging: quoting models of the Avellaneda–Stoikov class and extensions, multi‑asset inventory optimization, hedging, settlement workflows, real‑time risk limits and kill switches

• Maker‑taker economics and market‑quality measurement: fee‑tier and rebate architecture, per‑segment elasticity, spread/depth/slippage/markout metrics, defenses against rebate farming and wash trading
• Liquidity program design: obligation‑based schemes (two‑sided quoting, presence at touch, minimum depth, uptime) and incentive‑based schemes (tiered rebates, credit lines, connectivity benefits)
• Maker protection and flow segmentation: markout‑based counter party scoring, retail price improvement (RPI) order types, asymmetric speed bumps and latency floors, minimum quote life, self‑match prevention
• Exchange P&L modeling: net fee capture, subsidy budget and payback, LP unit economics from onboarding to self‑sufficiency

• Owner mentality with direct P&L accountability; ships to production and makes honest kill decisions
• Clear written communication with traders, engineers, exchange management, and external LPs
• Compliance discipline across crypto and Trad Fi market‑abuse regimes

• Design the program end‑to‑end: MM tiers, admission criteria, obligations (max spread, min depth, uptime, presence at touch), incentives, and graduation to subsidy‑free self‑sufficiency
• Optimize the fee schedule for net capture: taker tiers priced to measured elasticity by segment; maker rebates funded from taker fees; safeguards against tier gaming
• Design order‑book mechanics for comfortable quoting: tick and lot sizing, post‑only / iceberg / RPI order types, self‑match prevention, minimum quote life,…