The Ice Cream division at Unilever is preparing to stand on its own, aiming to become an independent, EUR 8.3 billion publicly listed company by the end of 2025. The Customer Analytics Data Scientist will empower the US Customer Development function to achieve its sales ambitions by developing advanced analytical models and insights.
Requirements
- 6+ years of experience with cloud data platforms (Azure, AWS, GCP) and Databricks, with strong proficiency in SQL, PySpark, Python, and DAX for building high-performance data transformations and pipelines.
- Hands-on experience with Databricks, Azure Data Factory, Delta Lake, Power BI, Alteryx and related cloud data technologies.
- Proficient in machine learning frameworks and libraries including scikit-learn, TensorFlow, PyTorch, XGBoost
- Experience with data visualization tools like PowerBI, Tableau.
- Strong understanding of data science principles and data visualization approaches
- Solid understanding of data modelling to support analytics and reporting use cases.
- Proficiency in coding languages such as Python, PySpark, DAX and SQL
Responsibilities
- Develop predictive and forecasting models (e.g., forecasting demand, pricing, promotions optimization, customer/shopper behavior) that drive commercial decision-making and business performance.
- Build advanced analytics capabilities including demand forecasting, promotion performance, assortment optimization, and shopper behavior modeling.
- Conduct advanced analytics analyses using data science, machine learning, and AI to uncover insights that generate tangible business value
- Communicate and deliver engaging data visualizations and data narratives that bring data to life for both technical & non-technical audiences, simplifying complex concepts and enabling decision-making across commercial teams.
- Work closely with business stakeholders to translate needs into well designed and executed technology products that are embedded into daily decision-making, with a focus on promotion optimization, syndicated and retailer data, demand forecasting, shopper marketing, digital commerce, and sales reporting
- Collaborate with data engineering to define consistent business logic and unified data definitions, consistent with how the business operates, that enable self-service analytics and integration across data products.
- Guide and lead squads or project teams, driving adoption of data science principles and best-in-class analytics approaches to deliver impactful solutions.
Other
- Full time, International sponsorship or relocation not supported
- Technical aptitude and the ability to lead teams toward business-value focused technology solutions
- Strong ability to communicate technical findings to non-technical audiences, turning data into actionable business narratives.
- Intellectual curiosity and strong analytic ability
- Preparedness to develop a deep understanding of business operations and needs for the Customer Development function
