Data Scientist
Bulgari
Posizione
Drive 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. Responsabilità del lavoro- Design, develop and validate advanced Machine Learning, Artificial Intelligence and predictive analytics models to address concrete business challenges and generate measurable business value.
- Build models for forecasting, recommendation, propensity/scoring, optimization, classification, clustering, anomaly detection, simulation and decision support.
- Analyse large, complex and heterogeneous datasets to identify patterns, drivers, risks, opportunities and actionable insights supporting strategic and operational decision-making.
- Apply statistical, econometric, machine learning and experimentation techniques, including model validation, performance evaluation and explainability approaches.
- Partner with business stakeholders and Data Factory actors to translate business needs into clear AI/ML problem statements, analytical approaches, success metrics and delivery priorities.
- Contribute to the qualification and prioritization of AI use cases by assessing feasibility, expected value, data readiness, scalability, risks and adoption requirements.
- Collaborate with business data teams and domain experts to ensure that model assumptions, input data, KPIs and outputs are meaningful, understandable and operationally usable.
- Design and improve scalable data science pipelines covering data preparation, feature engineering, experiment tracking, model training, validation, deployment and monitoring.
- Work with Data Engineering, Software Engineering, Enterprise Architecture and platform teams to integrate AI/ML solutions into production environments and enterprise applications.
- Ensure model lifecycle management practices, including versioning, reproducibility, CI/CD alignment, monitoring, drift detection, retraining triggers and controlled release management where applicable.
- Support the transition from proof of concept to production-grade AI products, avoiding isolated prototypes and contributing to reusable capabilities where appropriate.
- Contribute to the assessment, design and implementation of Generative AI and Agentic AI solutions, in collaboration with architecture, security, governance and business stakeholders.
- Evaluate the appropriate use of foundation models, RAG patterns, agents, orchestration frameworks, internal knowledge bases and business rules depending on the use case.
- Ensure AI solutions comply with internal governance, documentation, validation, security, privacy, data governance and Responsible AI standards throughout the lifecycle.
- Contribute to Responsible AI assessments, model documentation, auditability, transparency, explainability, human oversight and risk mitigation.
- Produce clear presentations, reports, dashboards and visual explanations to communicate technical findings, recommendations and business implications to technical and non-technical stakeholders.
- Support adoption by explaining how AI/ML outputs should be interpreted and embedded in business processes.
- Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Mathematics, Statistics, Engineering, Physics, Operations Research or another quantitative discipline.
- Proven experience in Data Science, Machine Learning, predictive analytics or applied AI in complex business and technology environments.
- Experience bringing analytical or AI solutions beyond experimentation into business adoption or production use is strongly preferred.
- Strong knowledge of statistics, supervised and unsupervised learning, predictive modelling, optimisation, experimentation and model validation.
- Advanced programming skills in Python and hands-on use of data science / ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch or equivalent.
- Strong SQL skills and experience working with large-scale data processing, cloud analytics and enterprise data platforms.
- Experience with model deployment, MLOps practices, CI/CD, Git-based version control, experiment tracking, model monitoring and reproducible development.
- Familiarity with Generative AI, LLMs, RAG, prompt engineering, agentic patterns and frameworks such as OpenAI APIs, Gemini, LangChain or equivalent is a strong advantage.
- Strong analytical and problem-solving skills, with the ability to translate complex business challenges into practical AI-driven solutions.
- Business curiosity and ability to understand processes, KPIs and decision flows before selecting technical solutions.
- Excellent communication and presentation skills, with the ability to explain complex technical topics to both technical and non-technical stakeholders.
- Strong collaboration and stakeholder management across multidisciplinary and international teams.
- Curiosity, innovation mindset and passion for emerging AI technologies, while maintaining rigour, pragmatism and delivery focus.
- High ownership, accountability and commitment to quality, documentation and continuous improvement.
Offerta di lavoro pubblicata 2 mesi fa