Role Overview:
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
Required Skills and Experience:
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)