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Quantitative Analyst Intern (Digital Assets Market Making - HFT) - Brussels

KeyrockBrussels
Type
Internship
Work setup
Remote
Experience
Junior
Posted
4 days ago
🌍 Fully remote

What research roles in crypto pay

36 salaries · our own data
median $143k$78k$217k

Most research roles in crypto pay between $78k and $217k, with a median of $143k.

As a Quantitative Analyst Intern on the Digital Assets Market Making (HFT) team at Keyrock, you will work alongside quantitative researchers, traders and engineers to analyse market and trading data, test hypotheses through backtesting and simulation, and build tools that improve strategy performance and risk visibility. You will investigate how fair value, liquidity, latency, queue position, fees and adverse selection affect real-world execution across the 80+ centralized and decentralized exchanges where Keyrock provides liquidity. This is a technical and applied internship: you will combine strong quantitative reasoning and coding skills with a detailed understanding of electronic markets, studying how exchanges work beneath the interface and connecting market microstructure to trading outcomes.

What you'll do

  • Analyse multi-venue top-of-book and depth data, trades, orders, fills and cancels to study liquidity, price discovery and execution quality
  • Build and validate latency-aware, event-driven backtests with explicit assumptions around maker/taker execution, queue position, fill probability, fees and cancellations
  • Measure spread capture, forward markouts, fees and adverse selection, and investigate how execution quality changes across venues, instruments and market regimes
  • Build reusable Python tools and data pipelines using modern columnar analysis and SQL for strategy research, performance attribution and monitoring
  • Study cross-venue price discovery, lead-lag relationships, fair-value construction and spot-perpetual basis while accounting for data staleness, instrument design and settlement-currency differences
  • Support live strategies through PnL, inventory and exposure analysis, post-trade review and investigation of unexpected performance
  • Evaluate liquidity-program economics by balancing execution quality, market share, fees and incentives, and work with traders and engineers to translate research into robust production improvements
  • Present findings clearly, including assumptions, limitations, risks and recommended next steps

What you bring

  • You are pursuing or recently completed a degree in mathematics, computer science, engineering, physics, quantitative finance or a related field
  • Proficiency in Python for data analysis, ideally including Polars or similar columnar tools, and comfort with SQL, Git and command-line workflows
  • Understanding of limit order books, order types, maker/taker mechanics, matching and priority rules, spreads, market depth and how trades move prices
  • Ability to reason about the order lifecycle from signal to acknowledgement and fill, including exchange APIs, latency, queue position, partial fills, cancellations, fees, slippage and adverse selection
  • Understanding of key differences between spot and perpetual futures, including basis, funding, leverage, liquidation risk, settlement currencies and residual exposure
  • Comfort with probability, statistics, time-series analysis and evaluating noisy results without overstating significance
  • Natural questioning of whether an apparent edge survives latency, fees, market impact, changing liquidity and real execution constraints
  • Ability to structure an ambiguous problem, test assumptions and communicate findings and limitations clearly in English
  • Ideally, you have built or analysed something yourself such as an order-book study, trading bot, exchange connector, backtest, execution simulator or market-data pipeline

Nice to have

  • Experience working with exchange WebSocket or REST APIs and asynchronous market-data pipelines
  • Exposure to Rust or another systems programming language
  • Experience with tick or order-book data, event-driven simulation or execution modelling
  • A technical project demonstrating sustained interest in systematic trading or market microstructure
  • Experience with ClickHouse or another analytical database

What we offer

  • A 6-month paid internship at Keyrock with accommodation provided for the entirety or part of it
  • The opportunity to learn about digital assets and blockchain from a comprehensive view of the entire ecosystem
  • Working from one of Brussels' newest and most advanced office spaces
  • A global, collaborative and tech-driven environment
  • Autonomy and impact through our flat structure, allowing you to contribute ideas from day one
  • Mentorship and dedicated guidance with regular feedback from experienced colleagues
  • The internship is based predominantly in Brussels; London is possible for a selected candidate, provided at least 1-2 months of onboarding is spent in Brussels with the rest of the cohort

About Keyrock

Since 2017, Keyrock has been a change-maker in digital assets, providing liquidity across 80+ centralized and decentralized exchanges. The company is a global, remote-first team of 200+ people across 40+ nationalities, with hubs in Brussels, London, Paris and New York, backed by Series C funding led by SC Ventures. Keyrock runs a full spectrum of capital markets businesses across centralized and on-chain venues: market making, high-frequency trading, options, OTC, DeFi trading desks, advisory and asset management.

Context for this role

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Keyrock on CryptoJobsHQ

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