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, scalability, quality, and distribution of the libraries developed by quantitative teams.
Responsibilities
- Collaborate with quantitative teams across different competence lines to understand methodological requirements and translate them into industrialized software components.
- Lead the engineering of models, algorithms, and quantitative libraries developed by research teams, ensuring robustness, scalability, quality, and maintainability.
- Ensure the effective integration of methodological and modeling components into product libraries and frameworks, including, where required, contributing directly to their implementation.
- Define architectures, development standards, testing practices, and delivery processes for quantitative software.
- Support other quantitative developers with design activities, code reviews, troubleshooting, and code quality improvements.
- Contribute to the evolution of ModelOps processes.
- Contribute to the evolution of quantitative library development processes through the pragmatic adoption of AI‑assisted tools for coding, testing, documentation, and maintenance.
- Collaborate with the product team in defining engineering and delivery processes for Prometeia's quantitative libraries.
Technical Skills (Must‑have)
- Advanced Python skills in scientific and numerical computing contexts.
- Strong proficiency in pandas and numpy.
- Significant experience with Spark/PySpark in the development and maintenance of distributed processing pipelines and libraries.
- Experience designing and maintaining Python libraries intended for enterprise use.
- Experience in industrializing quantitative models and transforming analytical prototypes into production‑grade solutions.
- Knowledge of software engineering practices, CI/CD, testing, and packaging.
- Knowledge of ModelOps principles applied to quantitative models and analytical libraries.
- Ability to effectively interact with quantitative stakeholders.
Nice‑to‑have
- Experience with complex analytical projects in risk management, credit, climate risk, or related quantitative domains; knowledge of relevant quantitative methodologies.
- Experience with Docker and reproducible development/deployment environments.
- Experience with GitHub Actions, GitLab CI, Azure DevOps, or equivalent tools.
- Modern Python packaging experience (pyproject.toml, wheels, semantic versioning).
- Experience coordinating technical activities or mentoring developers and quantitative researchers.
- Experience defining development standards and engineering processes for multidisciplinary teams.
- Advanced technical documentation skills (MkDocs, Sphinx, publishable notebooks, operational guides).
- Professional proficiency in English.
Requirements
- Scientific degree (Mathematics, Statistics, Physics, Engineering, Computer Science, Quantitative Economics, or related fields).
- High level of seniority, strong autonomy in decision‑making, and ability to drive technical standards and choices.
- Ability to provide technical coordination and collaborate across quantitative, product, and delivery teams.
What we offer
Our compensation package includes a fixed salary and a variable component, a comprehensive welfare plan, and a range of benefits to support our employees' well‑being.
We offer flexible remote working arrangements to promote work/life balance and reduce environmental impact.
Ongoing training is a priority – we provide an average of 11 days of training per year, both in person and online, and focus on continuous learning for every employee.
#J-18808-Ljbffr
or continue with email
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, scalability, quality, and distribution of the libraries developed by quantitative teams.
Responsibilities
- Collaborate with quantitative teams across different competence lines to understand methodological requirements and translate them into industrialized software components.
- Lead the engineering of models, algorithms, and quantitative libraries developed by research teams, ensuring robustness, scalability, quality, and maintainability.
- Ensure the effective integration of methodological and modeling components into product libraries and frameworks, including, where required, contributing directly to their implementation.
- Define architectures, development standards, testing practices, and delivery processes for quantitative software.
- Support other quantitative developers with design activities, code reviews, troubleshooting, and code quality improvements.
- Contribute to the evolution of ModelOps processes.
- Contribute to the evolution of quantitative library development processes through the pragmatic adoption of AI‑assisted tools for coding, testing, documentation, and maintenance.
- Collaborate with the product team in defining engineering and delivery processes for Prometeia's quantitative libraries.
Technical Skills (Must‑have)
- Advanced Python skills in scientific and numerical computing contexts.
- Strong proficiency in pandas and numpy.
- Significant experience with Spark/PySpark in the development and maintenance of distributed processing pipelines and libraries.
- Experience designing and maintaining Python libraries intended for enterprise use.
- Experience in industrializing quantitative models and transforming analytical prototypes into production‑grade solutions.
- Knowledge of software engineering practices, CI/CD, testing, and packaging.
- Knowledge of ModelOps principles applied to quantitative models and analytical libraries.
- Ability to effectively interact with quantitative stakeholders.
Nice‑to‑have
- Experience with complex analytical projects in risk management, credit, climate risk, or related quantitative domains; knowledge of relevant quantitative methodologies.
- Experience with Docker and reproducible development/deployment environments.
- Experience with GitHub Actions, GitLab CI, Azure DevOps, or equivalent tools.
- Modern Python packaging experience (pyproject.toml, wheels, semantic versioning).
- Experience coordinating technical activities or mentoring developers and quantitative researchers.
- Experience defining development standards and engineering processes for multidisciplinary teams.
- Advanced technical documentation skills (MkDocs, Sphinx, publishable notebooks, operational guides).
- Professional proficiency in English.
Requirements
- Scientific degree (Mathematics, Statistics, Physics, Engineering, Computer Science, Quantitative Economics, or related fields).
- High level of seniority, strong autonomy in decision‑making, and ability to drive technical standards and choices.
- Ability to provide technical coordination and collaborate across quantitative, product, and delivery teams.
What we offer
Our compensation package includes a fixed salary and a variable component, a comprehensive welfare plan, and a range of benefits to support our employees' well‑being.
We offer flexible remote working arrangements to promote work/life balance and reduce environmental impact.
Ongoing training is a priority – we provide an average of 11 days of training per year, both in person and online, and focus on continuous learning for every employee.
#J-18808-Ljbffr
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