DATA SCIENTIST
Pubblicato il 15-08-2026 - Unicredit in Italia
Overview We are looking for an experienced Senior Data Scientist to lead the creation of predictive AI solutions, leveraging Machine Learning and Big Data capabilities. You will be involved in the full E2 E development lifecycle of our ML solutions, from data architecture design to final delivery and production maintenance. You will also contribute to the development of our internal central assets, such as the feature store and shared libraries, through our MLOps framework. The solutions you will work on will impact important bank processes (e.g. credit evaluation, KYC, CRM) and will be built fully aligned with regulatory requirements (GDPR, AI Act, ECB guidelines). Responsibilities Design and develop predictive AI solutions by applying advanced ML and big data techniques. Define data architectures and pipelines to support scalable AI solutions. Train, evaluate, and optimize Machine Learning models for real-world applications. Develop and maintain centralized AI assets, including feature stores and shared libraries.
Integrate and manage ML solutions within our MLOps framework for seamless deployment. Squad service model adoption following Spotify schema Adopt an operative framework with regulatory requirements fully embedded, fully awareness of regulation updates Collaborate with multiple teams across the bank and countries (Data Platforms, Digital factories, Risk, Finance, Compliance functions, Cross countries CRM) in ideation, development and deployment phase Smart young team fully engaged in revolution the bank Qualifications University degree in Computer Science, Engineering, Mathematics, or Statistics. 4+ years of relevant experience in Data Science, AI, or ML Engineering. Advanced proficiency in Python and experience with big data engineering practices. Strong knowledge of ML and deep learning frameworks (Tensor Flow, Py Torch, Scikit-learn). Hands-on experience with third-party data platforms (Databricks, Palantir Foundry, Dataiku, etc.). Expertise in MLOps f