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

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.