Company: Wise Australia Investments
Location: London
Job Description:
Lead Data Scientist – Treasury Markets Quant
Join our Treasury Markets Data Science team to own and operate the production infrastructure behind our FX pricing, risk, and trading systems. Your work will directly impact Wise’s mission and millions of customers worldwide.
Responsibilities
- Python microservices that run quantitative models in production
- Monitoring, alerting, and reliability for real‑time pricing and risk systems
- Shared quant libraries used across multiple services
- CI/CD pipelines, deployment and operational excellence
- Incident response and root‑cause analysis for production issues
Growth Opportunities
- Real‑time curve construction (yield curves, FX forwards, vol surfaces)
- Pricing models for new instruments and products
- Trading strategy development and optimisation
- Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)
- Backtesting frameworks and model validation
- Customer behaviour modelling, pricing strategy and product launch support
- Collaboration with product teams to translate quantitative insights into customer‑facing decisions
Qualifications
- 4+ years building and maintaining production Python systems
- Strong experience with microservices, databases, and production infrastructure
- Experience with streaming systems, real‑time data pipelines, or event‑driven architectures (Kafka, Flink, Redis, etc.)
- Quantitative background in maths, physics, engineering, or finance – ability to read a model and reason about correctness
- Experience with testing, monitoring, and debugging complex systems under load
- Product mindset – think about who uses your systems and why
- Clear communicator who can work cross‑functionally with quants, analysts, traders, product managers, and engineers
- Bonus: familiarity with FX or financial markets experience
- Bonus: term‑structure modelling, stochastic calculus or Monte Carlo methods
- Bonus: interest rate curve bootstrapping
- Bonus: algorithmic execution experience
- Bonus: data lake or warehouse experience (Snowflake, Iceberg, Spark, etc.)
We’re people without borders – without judgement or prejudice, too. We want to work with the best people, no matter their background.
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Posted: July 13th, 2026