Senior Data Scientist - Retail Merchandising

04 ago - Romano di Lombardia
Experteer Italy

Overview

Senior Data Scientist to lead end-to-end data science initiatives in Retail and DTC Category Management & Merchandising. You will translate business needs into scalable AI solutions, shaping analytics strategy and enabling data-driven decisions across the organization. You’ll collaborate with business and AI teams to advance advanced analytics capabilities and deliver measurable impact. This role offers the opportunity to drive innovation in a global, fast-paced environment with iconic brands.

Responsibilities

- Design, develop, and deploy advanced data science and AI solutions (ML models, forecasting, optimization)
- Build AI-powered tools for retail and assortment use cases (recommendations, forecasting, decision engines)
- Explore Generative AI and multi-agent solutions with Corporate AI team
- Lead end-to-end data science projects from framing to deployment and monitoring on Databricks (PySpark, MLflow)
- Translate complex problems into scalable analytical solutions with measurable impact
- Collaborate with stakeholders to identify high-value opportunities for innovation
- Coordinate with Corporate Data & AI teams for robust implementations
- Contribute to best practices,



reusable frameworks for analytics and AI
- Mentor junior colleagues and drive knowledge sharing
- Develop dashboards to monitor adoption of tools and solutions

Requirements
- Degree in Data Science, Computer Science, Engineering, Mathematics, or related fields
- 4–7+ years of hands-on data science/AI project delivery
- Strong Python programming and DS/ML frameworks (pandas, scikit-learn, PyTorch)
- Advanced SQL and relational/lakehouse data models
- Production experience deploying ML models on Databricks (PySpark, MLflow)
- Experience xysqume with forecasting, optimization, NLP, and recommender systems
- Ability to translate business needs into technical solutions with impact
- Excellent communication and collaboration skills
- Mentoring ability and independent problem-solving
- Familiarity with cloud platforms and MLOps practices (nice to have)

Benefits
- Access to Leonardo learning platform
- Flexible work conditions
- Health insurance coverage
- Meal vouchers/ticket restaurants
- Internal rooftop canteen
- Employee discounts on eyewear and care products

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