Job description
The Innovation, AI & IT Governance division leads Generali Asset Management’s digital evolution by driving the adoption of innovative IT, Machine Learning, and AI solutions within a strong governance and regulatory framework. The unit oversees the development, integration, and evolution of digital platforms that support core business processes.
Its mission is to execute the Company’s technology innovation strategy, developing scalable ML and AI solutions and applied research initiatives, with a particular focus on algorithmic signal generation for portfolio construction and investment decision-making. The division ensures the transition from research to production, coordinates digital partners, and strengthens client-facing digital capabilities.
The team monitors market trends and AI adoption, promotes reusable solutions, and acts as a catalyst for business transformation by supporting new operating models, change management, and AI awareness across the organization.
We are looking for a brilliant Quant Data Scientist to join the Innovation and AI team of Generali Investments. The candidate will take part in AI projects and initiatives having the opportunity to gain full knowledge on AI applications, implementation, and delivery in the asset management business.
In particular the candidate will be responsible for the continuous research, development, and implementation of quantitative predictive models applied to financial markets, with the objective of enhancing portfolio performance and/or reducing risk over monthly, quarterly, semi-annual, and event-driven rebalancing horizons. The research and investment activities span multiple asset classes, including equities, fixed income (both government and corporate), and multi-asset portfolios. The candidate will contribute to deliver analytical projects, developing reusable AI products/solutions, scouting new technologies and methodologies, providing technical advisory and training for and in collaboration with other functions. The team works in close collaboration with other areas, in particular with portfolio managers, risk managers, and IT teams, contributing to investment decision-making processes and to the industrialization of the developed solutions.
The selected candidate will be involved in the following activities:
- Ongoing maintenance and enhancement of models and codebases
- Optimization of computational routines and refactoring activities, including potential rewriting of critical components in other languages (e.g., from Python to C++)
- Implementation, validation, and monitoring of research ideas within an existing quantitative framework
- Integration and deployment of code in Cloud environments
- Consultation of the relevant scientific literature, replicating and applying published results within the firm’s asset‑management modeling pipelines (where applicable)