Quant Developer

2 settimane fa

Milano, Lombardia, Italia Hunter Bond A tempo pieno

We are working with a fast-growing quantitative investment fund at an early but well-capitalised stage, looking to hire a Quant Developer / Data Engineer to help build and scale their data platform supporting systematic equity and futures strategies.

This is a highly technical role sitting close to the investment process, offering real ownership over market data infrastructure used in both research and live trading.

As a Quant Developer / Data Engineer, you will play a key role in the acquisition, ingestion, and processing of large-scale financial datasets. You'll work closely with quantitative researchers to ensure data is robust, clean, and production-ready.

Key responsibilities include:

  • Designing and maintaining data pipelines for market and alternative data
  • Supporting historical backtesting and production deployment across equities and futures
  • Managing data quality, validation, and versioning
  • Optimising storage and retrieval for research and live systems
  • Contributing to scalable, low-latency infrastructure in a startup environment

We're looking for candidates with a strong background in financial data engineering, ideally within systematic trading or quant research environments.

You should have experience with:

  • Equity statistical arbitrage datasets, including core market data (Bloomberg, Refinitv, FactSet)
  • Working with alternative datasets (e.g. fundamentals, events, sentiment, signals)
  • Large-scale time series data and cross-sectional datasets
  • Building data systems that support both research and production workflows

Technical Skills

  • Strong programming skills (Python essential; C++/Java a plus)
  • Experience with databases, data lakes, or columnar storage
  • Familiarity with cloud-based or distributed systems
  • Solid understanding of market data structures for equities and futures

Why Join?

  • Start-up culture with genuine roadmap to $1billion AUM
  • Equity on offer alongside excellent base plus bonus
  • Machine learning is core to the investment process, not an overlay
  • Exposure to multiple asset classes within a unified research framework
  • Opportunity to influence model design, data architecture and research standards

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