Responsibilities

• Implement, deploy, and maintain quantitative models for portfolio construction, risk, factor analytics, and systematic strategies in production.
• Design and maintain scalable Python infrastructure for backtesting, optimisation, and live analytics, with strong testing and CI/CD practices.
• Translate research methodology into production systems – portfolio optimisation, factor risk models, covariance estimation – using libraries such as CVXPY or Mosek.
• Work with portfolio managers, researchers, and IT to translate research designs into deployable production‑quality code.
• Maintain and improve the team's analytical infrastructure and engineering practices; stay current with relevant developments.

Qualifications

• Master's or PhD in a quantitative field (Computer Science, Mathematics, Statistics, Engineering, Physics, Finance, or related).
• 5+ years in quantitative developer o...