Senior Associate - Azure Data Engineer

Role Overview: 
We are looking for a Data Savvy / Data Science Product Manager with a strong foundation in retail supply chain and hands-on experience in creating and working with data platforms and data science to join our team.  

The Data Science Product Manager is an important architect in establishing the direction of data-centric innovation in Product Management within them Retail Supply Chain Domain. They are essential in the design, development and optimization of data-driven solutions that satisfy customer expectations and smoothly connect with Company & Supply Chain objectives. This role sits at the intersection of product, data science, and supply chain operations.  

You will work together with engineers and other data scientists in cross-functional teams to develop and deliver data products within the Supply Chain Domain. You will be skilled in business strategy, data analytics/data science, and product management. You will put the demands of users first, support data governance and quality, set up relevant performance evaluation criteria and explain the benefits of data products to a number of stakeholders. You will lead the definition and delivery of data and AI-driven opportunities within existing products to improve inventory health, planning efficiency, and end-to-end visibility. 

Responsibilities: 

• Translate business problems into data product opportunities, particularly in areas like inventory optimization and supply planning. 

• Creating use cases for improving/optimising Retail Supply Chain using data-driven and data-intensive approaches 

• Partner with data engineers and analysts to identify and evaluate AI/ML use cases across the supply chain (e.g., dynamic safety stock, predictive out-of-stock detection, lead time prediction, etc). 

• Help define the data platform strategy in SC, define and maintain product roadmaps for internal data products (dashboards, APIs, models) that drive measurable operational improvements. 

• Design and own the end-to-end lifecycle of data products: problem scoping, data exploration, model integration, and business adoption. 

• Ensure data availability, quality, and usability by collaborating closely with data engineering and governance teams. 

• Develop SQL queries and basic Python notebooks to explore, validate, and prototype data insights independently. 

• Define metrics to track product adoption, performance, and business impact; continuously iterate based on feedback and results. 

Required Skills & Experience: 

• Aware of and embrace platform thinking to view supply chain and enterprise inventory as an outcome of ecosystem wide interactions and model product solutions that encourage modularity, reusability and facilitate information sharing. 

• 10+ years in product management with strong exposure to data & analytics; at least 2+ years in a retail or supply chain setting. 

• Experience in driving Discovery to identify problems and opportunities in Retail Supply Chain through data analysis. 

• Ability to express what data-led KPIs are being driven and focus the development efforts toward providing that value. 

• Must be aware of external trends and be able to assess if and where they fit on our product agenda or how they can drive our business forward 

• Working knowledge of AI/ML concepts and their applications in supply chain (no model building expected, but familiarity with pipelines and model outputs is needed). 

• Strong proficiency in SQL, data visualization tools (e.g., Power BI, Tableau), and comfort with Python for data exploration. 

• Experience working with data lakes, APIs, and event-driven architectures. 

• Ability to write clear Requirements and collaborate with technical teams (data engineering, data science, supply chain operations). 

• Familiarity with demand/supply planning systems (e.g., Blue Yonder, SAP IBP) is a plus. 

• Experience in building / implementing Control Towers / SC Visibility platforms