DeFi Quant Research Intern – Digital Assets Market Making
A six-month research internship on the strategic proprietary market making desk, focused on on-chain (DeFi) markets. You would work with researchers, traders and engineers to study how blockchain mechanics shape liquidity, execution and strategy performance.
What you’d work on
Our reading of the posting: what a new hire in this role would most likely spend their first months on.
- Analyse on-chain liquidity and price formation on AMMs and other decentralised venues
- Backtest and simulate DeFi trading ideas, including the cost of gas, slippage and transaction ordering
- Build reusable Python tools and data pipelines for research and monitoring
- Compare centralised and decentralised prices to inform hedging and pricing
- Do post-trade analysis on live strategies and explain unexpected PnL
What they ask for
Required
- Python for data analysis
- SQL, Git and command-line workflows
- Working knowledge of blockchain transactions, gas and finality
- AMMs, concentrated liquidity, oracles and liquidations
- MEV awareness (arbitrage, backrunning, sandwiching)
- Probability and quantitative reasoning
- Clear written and spoken English
Preferred
- Querying chain data via RPCs, indexers or subgraphs
- Reading Solidity and event logs
- Rust or another systems language
- Non-EVM chains or Layer 2 execution models
- A personal on-chain or DeFi project
- Education
- Current or recent degree in maths, computer science, engineering, physics, quantitative finance or a related field
- Experience
- Students or recent graduates, ideally with hands-on DeFi projects
- Languages and tools
- Markets
- crypto
How to prepare
- Build an AMM simulator (constant product and concentrated liquidity) and measure impermanent loss and slippage
- Pull on-chain swap data from an indexer or subgraph and study price impact and arbitrage gaps against a centralised venue
- Read about MEV, block construction and transaction ordering, then model how it erodes a simple arbitrage edge
- Write a backtest that charges gas, fees and latency, and test whether an apparent edge survives them
What to study
- Python for Quantitative Finance
- Market Microstructure and Execution
- Quantitative Research, Data and Backtesting
- Probability, Statistics and Financial Data
The Quantitative Researcher roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on Keyrock’s site before applying: requirements, location and pay can change after we check them.
View the posting on Keyrock’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Keyrock and doesn’t handle applications.