Data Scientist

**Job Description: Data Scientist - Artificial Intelligence** **Location**:

Turin **Overview** **Key Responsibilities** **AI & Machine Learning Expertise** - Design, build, and deploy advanced machine learning models, from supervised learning to deep learning architectures, addressing key business challenges such as risk scoring, fraud detection, and automation. - Contribute to the research and prototyping of **Agentic AI solutions**, including autonomous agents for task orchestration, workflow automation, or adaptive reasoning in enterprise settings. - Ensure robustness, scalability, and fairness in all model developments, aligning with MLOps practices and ethical AI frameworks. **End-to-End Solution Development** - Translate business problems into data science solutions and guide the full lifecycle: from exploration and experimentation to validation, deployment, and monitoring. - Collaborate closely with data engineers, software developers, and enterprise architects to integrate AI solutions into production environments, primarily on Azure. - Define and implement metrics for evaluating model performance, business impact, and alignment with strategic goals. **Cross-functional Collaboration & Thought Partnership** - Act as a trusted expert within cross-functional teams, including actuarial, claims, marketing, and IT. - Support the mentoring of junior team members by sharing expertise, code reviews, and leading best practices. - Partner with colleagues across international teams (e.g., Spain) to co-develop scalable AI assets and foster knowledge exchange. **Qualifications** **Education** - Master’s or Ph.

D. in Data Science, Artificial Intelligence, Computer Science, Engineering, Mathematics, or a related quantitative field. **Experience** - 3+ years of experience in advanced data science roles with a strong track record of delivering AI-powered solutions in production. - Practical experience in **Generative AI and/or Agentic AI**systems (e.g., using Open

AI APIs, Lang

Chain, orchestration frameworks). - Solid exposure to enterprise environments, preferably in insurance, financial services, or other regulated industries. **Technical Skills** - Advanced programming skills in Python (mandatory), with knowledge of common ML and DL libraries (scikit-learn, Py

Torch, Tensor

Flow, transformers). - Strong experience in model lifecycle management, evaluation techniques, and versioning (e.g., MLflow, DVC). - Proficiency in cloud-based ML ecosystems, especially Microsoft Azure (Azure ML, Data Factory, Cognitive Services). - Understanding of vector databases, LLM fine-tuning, and embedding-based retrieval is a strong plus. **Soft Skills** - Fluent in English; Spanish knowledge is a plus.