Lead Quantitative Developer (Python)
Are you curious and ready to take on a new career challenge? Are you eager to join a dynamic company and bring innovation through your work and skills? Prometeia offers opportunities for growth and training within a Group that serves more than 500 clients in 20 countries worldwide and has over 1,200 professionals. Among the European leaders in Enterprise Risk Management, Prometeia is looking for a Lead Quantitative Developer (Python) to join its internal development team.
Mission
- Lead the industrialization, evolution, and maintenance of Prometeia's quantitative libraries across the risk, climate, and credit domains, acting as a key link between quantitative research, software development, and delivery.
- The role will directly contribute to the development and evolution of quantitative frameworks,
the definition of engineering and ModelOps standards, and the transformation of library development and maintenance processes through the pragmatic adoption of AI-assisted development tools and practices.
- One of the key objectives of the role will be to support the evolution of the quantitative library lifecycle by introducing and consolidating AI-assisted development practices and tools to support code writing, testing, documentation, and software maintenance.
- The position is not focused on developing new quantitative methodologies or mathematical models, but rather on engineering, scalab
Mission
- Lead the industrialization, evolution, and maintenance of Prometeia's quantitative libraries across the risk, climate, and credit domains, acting as a key link between quantitative research, software development, and delivery.
- The role will directly contribute to the development and evolution of quantitative frameworks,
the definition of engineering and ModelOps standards, and the transformation of library development and maintenance processes through the pragmatic adoption of AI-assisted development tools and practices.
- One of the key objectives of the role will be to support the evolution of the quantitative library lifecycle by introducing and consolidating AI-assisted development practices and tools to support code writing, testing, documentation, and software maintenance.
- The position is not focused on developing new quantitative methodologies or mathematical models, but rather on engineering, scalab