Senior Research Engineer (1-year contract or till 30 June 2027), SCIS

Job description

Job Description This position is forSchool of Computing and Information Systems (SCIS). Design and develop software for risk analytics, scenario simulation, and optimisation workflows. Build Python-based data pipelines, APIs, analytics services, and internal tooling. Translate quantitative models into maintainable, production-ready code. Develop tools for Monte Carlo simulation, tail-risk estimation, VaR/CVaR analysis, and stress testing. Work with structured and unstructured financial, market, and client data. Support integration of quantum and quantum-inspired methods where commercially relevant. Improve code quality through testing, version control, and engineering best practices. Contribute to dashboards and client-facing analytics applications. Qualifications Minimum Bachelor's degree in Computer Science, Information Technology, Information Systems or closely related disciplines. Minimum 4 years of relevant experience. Strong programming skills in Python and Rust. Experience with Git, testing, CI/CD, and code review. Experience building APIs, backend services, or data-driven applications. Good understanding of numerical methods, statistics, and data handling. Comfortable with tools such as NumPy, Pandas, SciPy, and related tooling. Preferred: financial risk, portfolio analytics, Monte Carlo, optimisation, cloud, Docker, SQL/Postgres, dashboards, or quantum-related exposure. This position is forSchool of Computing and Information Systems (SCIS). Design and develop software for risk analytics, scenario simulation, and optimisation workflows. Build Python-based data pipelines, APIs, analytics services, and internal tooling. Translate quantitative models into maintainable, production-ready code. Develop tools for Monte Carlo simulation, tail-risk estimation, VaR/CVaR analysis, and stress testing. Work with structured and unstructured financial, market, and client data. Support integration of quantum and quantum-inspired methods where commercially relevant. Improve code quality through testing, version control, and engineering best practices. Contribute to dashboards and client-facing analytics applications.