Python Quant Developer - HFT Team

London

Permanent

Negotiable

Financial Technology

PR/564638_1760432184

We're working with a cutting-edge trading firm that's building a global financial institution for digital assets. Their mission is to bring integrity and efficiency to crypto markets through a disciplined, first-principles approach. With strong momentum and a rapidly growing footprint, they're expanding their high-frequency trading (HFT) team and looking for a Python Quant Developer to help scale their research and analytics infrastructure.

This role offers the chance to work directly with quant researchers and traders, owning the Python stack that powers strategy development, backtesting, and live trading.

Key Responsibilities

Own and evolve the internal Quant Research Experience (QRX) platform.
Collaborate with traders and researchers to develop and refine trading models.
Build high-quality research tooling for simulations, post-trade analysis, and visualizations.
Develop data pipelines for high-frequency and alternative market data.
Implement robust data validation, monitoring, and access layers.
Scale research pipelines into distributed compute jobs using frameworks like Dask and Ray.
Enhance Jupyter-based tooling for strategy prototyping and tuning.
Build performance attribution and diagnostic tools.
Create dashboards and visualizations for order book and strategy monitoring.

Ideal Candidate Profile

Must-Have Experience

5+ years of professional Python development.
Strong skills in writing clean, modern Python code.
Experience building and documenting developer-friendly APIs.
Deep familiarity with the Python data ecosystem (Pandas, Numpy, PyArrow, Bokeh, Matplotlib, IPyWidgets, Jupyter, etc.).
Proven experience with large-scale data pipelines and ETL workflows.
Comfortable working in Jupyter notebooks.
Understanding of crypto or traditional financial markets and trading concepts.

Nice-to-Have Experience

Experience with crypto exchanges and market microstructure.
Hands-on with interactive visualization libraries like Bokeh.
Distributed compute experience (Dask, Ray).
Exposure to ML frameworks (JAX, PyTorch, TensorFlow, XGBoost).
Experience with compilers or code generation.

Apply Now!

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