Back to the previous pageQuantitative Research Engineer (NY - Texas - Utah)
Location:
United Kingdom
Salary:
Competitive
Job Type:
Permanent
Date Posted:
35 minutes ago
Expiry Date:
14/10/2026
Job Ref:
127795
Start Date:
16/07/2026
Contact:
Craig Pearman
Contact Email:
craig.pearman@xcede.com
Specialism:
England
Quantitative Research Engineer
Location - New York (Noho) I London (Mayfair) I Texas (Austin) I Utah (Salt Lake City)
As a spin-out from Tudor Investment Corp, Xantium is launching a multi-strategy hedge fund focused on delivering consistent returns through innovative trading strategies, robust risk management, and cutting-edge technology.
We are looking for Quantitative Research Engineers to sit at the intersection of Portfolio Management and Quantitative Research. You will work directly with portfolio managers and quant researchers to translate investment ideas into robust, production-quality research workflows - building the tools, infrastructure, and frameworks that allow the desk to research, test, and deploy systematic strategies quickly and reliably.
Core requirements:
Location - New York (Noho) I London (Mayfair) I Texas (Austin) I Utah (Salt Lake City)
As a spin-out from Tudor Investment Corp, Xantium is launching a multi-strategy hedge fund focused on delivering consistent returns through innovative trading strategies, robust risk management, and cutting-edge technology.
We are looking for Quantitative Research Engineers to sit at the intersection of Portfolio Management and Quantitative Research. You will work directly with portfolio managers and quant researchers to translate investment ideas into robust, production-quality research workflows - building the tools, infrastructure, and frameworks that allow the desk to research, test, and deploy systematic strategies quickly and reliably.
- Partner directly with Portfolio Managers and Quant Researchers to scope, design, and build research workflows that support the full lifecycle of strategy development.
- Design, build, and maintain a robust backtesting framework covering signal generation, portfolio construction, transaction cost modelling, and performance attribution.
- Translate strategy and signal concepts from research into well-tested, production-grade code, ensuring a smooth and reliable path from idea to live implementation.
- Contribute directly to strategy and signal development — including data exploration, factor and alpha research, hypothesis testing, and statistical validation.
- Build and maintain data pipelines for market, fundamental, and alternative datasets, ensuring data quality, lineage, and reproducibility across research and production.
- Develop tooling for portfolio simulation, risk analytics, scenario analysis, and performance monitoring to support day-to-day Portfolio Management decision-making.
- Optimise the performance, scalability, and reliability of research and backtesting infrastructure, identifying and resolving bottlenecks.
- Collaborate with technology and infrastructure teams to ensure research tools integrate cleanly with the firm's broader trading and risk systems.
- Stay current with developments in quantitative methods, market microstructure, and research engineering best practice, proactively suggesting improvements.
Core requirements:
- Degree (or higher) in a highly quantitative discipline — Computer Science, Engineering, Mathematics, Physics, Statistics, or similar.
- Strong software engineering skills in Python (essential), with production-quality coding practices (testing, version control, code review, CI/CD).
- Proven experience building or maintaining backtesting frameworks, research platforms, or strategy simulation tools in a systematic trading or asset management environment.
- Solid grounding in statistics, time-series analysis, and quantitative finance concepts (factor models, portfolio construction, risk, transaction costs).
- Experience working with large financial datasets — market data, fundamentals, or alternative data — including cleaning, structuring, and validating data at scale.
- Comfortable working directly with Portfolio Managers and Researchers, translating investment intuition into clear technical requirements.
- Prior experience in a hedge fund, systematic asset manager, prop trading, or tier-1 investment bank.
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