Quantitative Analyst Intern (Digital Assets Market Making)

Location: On-site in Brussels, Belgium; London, United Kingdom is possible, provided 1–2 months of onboarding are spent in Brussels.

Company

hirify.global is a digital assets company providing liquidity and capital markets services across centralized and decentralized exchanges, including market making, high-frequency trading, options, OTC, DeFi trading, advisory and asset management.

What you will do

• Analyze multi-venue order-book, trade, order, fill and cancellation data to study liquidity, price discovery and execution quality.
• Build and validate latency-aware, event-driven backtests and simulations covering execution mechanics, queue position, fees, cancellations and fill probability.
• Measure spread capture, markouts, fees and adverse selection across venues, instruments and market regimes.
• Build reusable Python tools and data pipelines with columnar analysis and SQL for research, attribution and monitoring.
• Study cross-venue price discovery, lead–lag relationships, fair value and spot–perpetual basis.
• Support live strategies through PnL, inventory, exposure and post-trade analysis, and collaborate with traders and engineers on production improvements.

Requirements

• 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 with Polars or similar columnar tools, plus comfort with SQL, Git and command-line workflows.
• Understanding of electronic market structure, including limit order books, order types, maker/taker mechanics, matching and priority rules, spreads and market depth.
• Ability to reason about order lifecycles, exchange APIs, latency, queue position, partial fills, cancellations, fees, slippage and adverse selection.
• Understanding of spot and perpetual futures, including basis, funding, leverage, liquidation risk, settlement currencies and residual exposure.
• Comfort with probability, statistics and time-series analysis, including evaluation of noisy results without overstating significance.
• Ability to structure ambiguous problems, test assumptions and communicate findings, limitations and risks clearly in English.
• Strong curiosity about systematic trading and willingness to analyze or build relevant systems such as order-book studies, trading bots, exchange connectors, backtests, execution simulators or market-data pipelines.

Nice to have

• Experience 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.

Culture & Benefits

• Six-month paid internship with accommodation provided for all or part of the internship.
• Hands-on work with clear learning goals, dedicated guidance and regular feedback.
• On-site work in the Brussels office, with a London option after the Brussels onboarding period.
• Global, collaborative and technology-driven environment with autonomy and early contribution opportunities.
• Background checks are required and must be passed before joining.

Hiring process

• Apply by 30 November 2026; the internship starts on 1 March 2027.
• Selection includes an interview with Talent Acquisition, an interview with the Hiring Manager and a recruitment challenge.