The Quantitative Developer will design, implement, and maintain analytical models and processes, with a strong focus on Python development, leveraging statistical libraries, and utilising cloud platforms such as AWS, Azure and Snowflake for scalable deployment.
Key Responsibilities:
- Develop and optimise quantitative models and analytical tools in Python
- Leverage statistical g packages (e.g., pandas, NumPy) for data analysis and modelling
- Work closely with portfolio managers, researchers, and technology teams to deploy robust, scalable solutions
- Design and implement data pipelines and workflows utilising AWS or Azure infrastructures
- Ensure best practices in code quality, version control, and deployment automation
- Provide technical support and documentation for developed solutions
- Proven experience in Python programming for quantitative or analytical applications
- Strong proficiency with relevant statistical libraries Pyth
- Practical experience utilising AWS and/or Azure for deployment and workflow orchestration
- Solid understanding of financial data and modelling techniques (preferred)
- Excellent analytical, communication, and problem-solving skills
- Experience with data engineering & ETL tools such as Apache Airflow or custom ETL scripts.
- Strong problem-solving skills with a keen analytical mindset especially in handling large data sets and complex data transformations.
- Strong experience in setting up an underlying test framework for complex data calculations and processing.
- Strong familiarity with engineering and data architecture principles.
- Prior experience in a front office or financial services environment (desirable)