IT & Software

Quantitative Researcher / Developer (Data Science) - Treasury FX

Wise

London · Greater London · United Kingdom

Overview

You will join Wise’s Treasury FX Data Science team to develop and operate models and production systems for FX pricing, risk, and trading. You’ll help manage USD 250bn+ in annual FX volume, collaborating with quants, traders, analysts, product managers and engineers. The role blends quantitative modelling or engineering focus with production ownership to deliver scalable, real-time FX capabilities. You will shape risk analytics, pricing strategies and hedging approaches while partnering across functions to impact customer experiences. This is a hands-on, impact-driven chance to advance Wise’s mission of borderless money.

Responsibilities
  • Python implementation of quantitative work from research to production
  • Validate, backtest and monitor model and service performance
  • Deploy and respond to incidents; perform root-cause analysis and continuous improvement
  • Develop and maintain shared quant libraries used across services
  • Manage CI/CD pipelines, deployments and operational excellence
  • Monitor and ensure reliability of real-time pricing and risk systems
  • Grow knowledge in market data management and quant infrastructure design
  • Collaborate with engineering and product teams to translate insights into customer-facing decisions
Key requirements
  • 4+ years of quantitative or engineering experience with strong Python development
  • Background in maths, physics, engineering or finance and ability to reason about model correctness
  • Experience in FX or financial markets is a plus
  • Familiarity with term structure modelling, stochastic calculus or Monte Carlo methods is a plus
  • Knowledge of data lakes or warehouses (Snowflake, Iceberg, Spark) is a plus
  • Product mindset and ability to work cross-functionally with quants, analysts, traders, product managers and engineers
  • Experience taking quantitative work into production with ongoing validation and monitoring
  • clear communication
  • cross-functional collaboration
  • problem-solving with stakeholding teams
  • Python
  • quantitative modelling
  • backtesting

Reference: WJ-747_30818794

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