Quantitative Developer | Crypto Market Making
Our client are a research and trading firm building a tier‑1 high‑frequency trading platform. They design and operate systematic trading strategies in a fast‑paced, highly driven environment where new markets and opportunities appear quickly - and disappear just as fast. Many of their edges come from moving early: capturing arbitrage, basis, or structural inefficiencies before they are competed away.
The Role
You'll work closely with experienced traders and engineers, helping turn ideas into working systems under real‑time pressure. You'll start by building simple, fast prototypes and, as ideas prove themselves, help evolve them into reliable and scalable production components.
This is a hands‑on role for people who enjoy intensity, ownership, and learning by doing.
What You'll Do
- Implement trading ideas alongside senior traders in a rapid iteration loop
- Analyze market microstructure, order book dynamics, and exchange‑level data to identify and validate edges
- Build and backtest quantitative models for pricing, signal generation, and execution optimization
- Integrate with exchange and market data APIs, often under tight timelines
- Write Python code for trading logic, data ingestion, statistical analysis, and monitoring
- Work with databases to store and query large volumes of time‑series data
- Use Grafana to monitor system health, performance, and market behavior
- Debug real‑world issues such as API inconsistencies, latency, and data gaps
- Use LLMs (Claude, Codex, etc.) to accelerate development and problem‑solving
What They're Looking For
- Strong Python fundamentals; experience with
asyncio - Solid foundation in probability, statistics, and numerical methods - comfortable reasoning about distributions, hypothesis testing, and estimation
- Ability to think quantitatively about risk, PnL attribution, and edge sizing
- Familiarity with NumPy, pandas, and SciPy (or equivalent) for data analysis and modelling
- Strong LLM workflow
- High drive, curiosity, and comfort operating in a fast‑moving environment
- Willingness to make pragmatic trade‑offs and iterate quickly
- Ability to take direct feedback and improve fast
Nice to Have (Not Required)
- Background in a quantitative discipline (mathematics, physics, statistics, engineering, computer science)
- Experience with backtesting frameworks, simulation, or Monte Carlo methods
- Exposure to market microstructure concepts: spreads, slippage, maker/taker dynamics, funding rates
- Projects or coursework related to trading, finance, or systems engineering
- Experience with SQL, time‑series data, or real‑time systems
- Familiarity with stochastic processes, time‑series analysis, or signal processing
- Genuine interest in markets, crypto, or exchange mechanics
- Exposure to Python tooling such as
uv, type checkers, and linting
Must have UK right to work or be based remote in a similar timezone
Apply Now!
FAQs
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