Job Title: B&W R&D Data Office Data and Digital Analyst
Location: UK - Port Sunlight
Work Level: WL1-RH4

SPECIFIC SKILLS

• Science/Maths based Degree with business modules preferred.
• Strong Excel skills are essential (pivot tables, macros, VLOOKUP’s etc.)
• Data capture and manipulation experience preferred (e.g. Excel, PowerApps, Alteryx, ideally Python).
• Experience with data visualisation software would be advantageous (e.g. PowerBI/Seaborn/Matplotlib)
• Experienced in AI/GenAI project delivery.
• Experience in People Transformation / Training activities preferred.
• Experience with SAP / LIMS / CU PIRD preferred.
• Experience with Data Quality improvement projects preferred.
• Strong Python skills, clean coding practices would be an advantage.

MAIN JOB PURPOSE

This role supports the B&W R&D Data Office in unlocking insights and driving innovation through advanced analytics, AI, and digital programme management—enhancing decision-making and operational effectiveness across R&D functions. This includes analysing large volumes of data from varied sources, generating insights and ensuring those insights are acted upon in the business.

KEY TASKS

• Preparing complex data analyses for the B&W R&D Leadership Teams (BG, BU and S&T)
• Communicate results of ingredients, sales and portfolio data analyses to cross-functional groups (R&D, Supply Chain, Procurement, Quality, etc.)
• Support the B&W Data Office with Category related tasks such as Budget Management, KPIs, Sustainability etc.
• Use data handling skills to maintain and develop our Data Office reporting environment; quarterly update of published tools and bespoke development of new capabilities based on business need.
• Support the B&W Digital team in their People Transformation programme, driving Digital Upskilling and a Digital-First mindset in B&W R&D.
• Support B&W Strategy & Ops with relevant tasks
• Lead AI initiatives from concept to deployment for B&W R&D. Demonstrate leadership in the space of Agentic AI.
• Translate scientific challenges into tangible objectives and identify data-driven solutions.