Quantitative Analyst Intern - Digital Assets Market Making; HFT

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

Since 2017, Keyrock has been a change-maker in digital assets. We're a global, remote-first team of 200+ people across 40+ nationalities, with hubs in Brussels, London, Paris and New York.

We provide liquidity across 80+ centralized and decentralized exchanges - a position cemented by our Series C, led by SC Ventures. Today we run 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.

We're building toward the agentic investment banking capabilities for the era of digital finance. A proprietary agentic layer runs the mechanics of the market, so our people can focus on the work code cannot do: the deal, the relationship, and the judgement.

We're not just envisioning the future of finance - we're building it.

Our internship programme gives early-career talent the opportunity to build practical skills, contribute to meaningful projects and learn alongside experienced colleagues in digital finance.

Typically lasting six months and based in our Brussels office (London possible), each internship includes hands-on experience, clear learning goals and dedicated guidance and regular feedback. We look for curiosity, relevant foundational skills, deep, active interest and passion for digital assets and the potential to grow exponentially with us - you don't need to arrive with all the answers. Where performance, business needs and available opportunities align, an internship may lead to a permanent role, though this is not guaranteed.

We are looking for 3-4 high-caliber Quantitative Analyst Interns to sit within our Strategic Market Making (CeFi and DeFi), Credit and Corporate Development desks/teams (see other openings on our career page for details).

Final date to receive applications: 30 November 2026

Start date:

1 March 2027

Selection process:

• Interview with Talent Acquisition representative
• Interview with Hiring Manager
• Recruitment Challenge

The role

Our Strategic Proprietary Market Making team researches and deploys systematic trading strategies across centralized digital asset venues. We study how order-book dynamics, fragmented liquidity, exchange design and participant behaviour shape pricing, execution and risk.

As a Quantitative Analyst Intern within the HFT track, 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 venues.

This is a technical and applied internship. We are looking for someone who combines strong quantitative reasoning and coding skills with a detailed understanding of electronic markets. You should be curious about how exchanges work beneath the interface and able to connect market microstructure to trading outcomes.

• 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.