ph3Posizione /h3 pDrive the design, development, validation and industrialization of Data Science, Machine Learning and Artificial Intelligence solutions that transform business opportunities into scalable, governed and value-generating Data AI products. Within the central Data AI Product Unit, the Data Scientist partners with business stakeholders, Data Architects, Data Engineers, Data Domain Owners, Business Product Owners and Data Governance teams to identify high-value AI/ML use cases, build robust analytical solutions, and integrate them into enterprise processes and platforms. The role contributes to the Data AI transformation agenda by combining statistical rigour, technical excellence, business understanding, Responsible AI principles and production-oriented delivery across traditional AI/ML, Generative AI and Agentic AI initiatives. /p h3Responsabilità del lavoro /h3 ul liDesign, develop and validate advanced Machine Learning, Artificial Intelligence and predictive analytics models to address concrete business challenges and generate measurable business value. /li liBuild models for forecasting, recommendation, propensity/scoring, optimization, classification, clustering, anomaly detection, simulation and decision support. /li liAnalyse large, complex and heterogeneous datasets to identify patterns, drivers, risks, opportunities and actionable insights supporting strategic and operational decision-making. /li liApply statistical, econometric, machine learning and experimentation techniques, including model validation, performance evaluation and explainability approaches. /li liPartner with business stakeholders and Data Factory actors to translate business needs into clear AI/ML problem statements, analytical approaches, success metrics and delivery priorities. /li liContribute to the qualification and prioritization of AI use cases by assessing feasibility, expected value, data readiness, scalability, risks and adoption requirements. /li liCollaborate with business data teams and domain experts to ensure that model assumptions, input data, KPIs and outputs are meaningful, understandable and operationally usable. /li liDesign and improve scalable data science pipelines covering data preparation, feature engineering, experiment tracking, model training, validation, deployment and monitoring. /li liWork with Data Engineering, Software Engineering,



Enterprise Architecture and platform teams to integrate AI/ML solutions into production environments and enterprise applications. /li liEnsure model lifecycle management practices, including versioning, reproducibility, CI/CD alignment, monitoring, drift detection, retraining triggers and controlled release management where applicable. /li liSupport the transition from proof of concept to production-grade AI products, avoiding isolated prototypes and contributing to reusable capabilities where appropriate. /li liContribute to the assessment, design and implementation of Generative AI and Agentic AI solutions, in collaboration with architecture, security, governance and business stakeholders. /li liEvaluate the appropriate use of foundation models, RAG patterns, agents, orchestration frameworks, internal knowledge bases and business rules depending on the use case. /li liEnsure AI solutions comply with internal governance, documentation, validation, security, privacy, data governance and Responsible AI standards throughout the lifecycle. /li liContribute to Responsible AI assessments, model documentation, auditability, transparency, explainability, human oversight and risk mitigation. /li liProduce clear presentations, reports, dashboards and visual explanations to communicate technical findings, recommendations and business implications to technical and non-technical stakeholders. /li liSupport adoption by explaining how AI/ML outputs should be interpreted and embedded in business processes. /li /ul h3Profilo /h3 h3Technical Skills /h3 ul liBachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Mathematics, Statistics, Engineering, Physics, Operations Research or another quantitative discipline. /li liProven experience in Data Science, Machine Learning, predictive analytics or applied AI in complex business and technology environments. /li liExperience bringing analytical or AI solutions beyond experimentation into business adoption or production use is strongly preferred. /li liStrong knowledge of statistics, supervised and unsupervised learning,



predictive modelling, optimisation, experimentation and model validation. /li liAdvanced programming skills in Python and hands‑on use of data science / ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch or equivalent. /li liStrong SQL skills and experience working with large-scale data processing, cloud analytics and enterprise data platforms. /li liExperience with model deployment, MLOps practices, CI/CD, Git‑based version control, experiment tracking, model monitoring and reproducible development. /li liFamiliarity with Generative AI, LLMs, RAG, prompt engineering, agentic patterns and frameworks such as OpenAI APIs, Gemini, LangChain or equivalent is a strong advantage. /li /ul h3Soft Skills /h3 ul liStrong analytical and problem‑solving skills, with the ability to translate complex business challenges into practical AI‑driven solutions. /li liBusiness curiosity and ability to understand processes, KPIs and decision flows before selecting technical solutions. /li liExcellent communication and presentation skills, with the ability to explain complex technical topics to both technical and non‑technical stakeholders. /li liStrong collaboration and stakeholder management across multidisciplinary and international teams. /li liCuriosity, innovation mindset and passion for emerging AI technologies, while maintaining rigour, pragmatism and delivery focus. /li liHigh ownership, accountability and commitment to quality, documentation and continuous improvement. /li /ul h3Informazioni aggiuntive per i candidati /h3 pFor new joiners in this role in Italy, the initial annual gross salary is EUR 50.000. /p pThis salary has been determined on the basis of objective and gender‑neutral criteria and corresponds to the compensation normally granted for this position at the time of publication of this job posting. Actual compensation may vary depending on factors such as your unique combination of experience and skills, seniority, and current organizational needs. /p pIn addition to the benefits provided by law, further benefits may be granted in accordance with current company policies. /p pThe employment relationship will be governed by the provisions of the applicable national collective bargaining agreement (CCNL Terziario, Distribuzione e Servizi), as applied by Bulgari in Italy. /p /p #J-18808-Ljbffr

📌 Data Scientist (Roma)
🏢 Bvlgari
📍 Roma