Fabric Enhancers R&D Data Analyst

Please Note: The deadline for applying is 23.59 the day before the job posting end date.

Job Title: Fabric Enhancers R&D Data Analyst

Location: Port sunlight Research Lab

Work-Level: RH4

Fabric Care is one of the biggest categories in Unilever and the largest category in HomeCare (HC). Consisting of Fabric Cleaning and Fabric Enhancers (FE), it has some highly loved brands including Dirt4 Good, Surf, Comfort and Snuggle. 

The FE team, based in Port Sunlight, develops exciting product innovations, with a strong focus on solving consumer pain points with differentiated mixes, crafted from technology for superior performance and delivering our Clean Future promise.  It is a fast-paced category with a truly exciting transformational agenda and vision for future growth.

JOB PURPOSE 

Our aim is to become the world’s most admired HC company powered by Clean Future. An ambitious digital transformation agenda with rigorous execution is a critical enabler to realize our vision. We are transforming the speed and quality of product innovation to deliver product superiority faster through the power of digital.

RESPONSIBILITIES 

In FE R&D, we focus on developing and deploying the digital capabilities to deliver 4 key business goals: clean future innovation, win with consumers, reduce cost & complexity and agile implementation. Part of the FE R&D Digital Team, the R&D Data Analyst will play a key role in the increased confidence in data driven decisions across FE R&D, through the identification, definition and execution of priority data analytics and visualisation solutions and support.

ALL ABOUT YOU 

Key Skills

📊 1. Data Management & Integration

Core Skills:

• Ability to manipulate and manage complex datasets.
• Proficient in linking and integrating data from multiple sources.
• Strong understanding of data structures, storage, and organization.

Tools & Technologies:

• Power BI: Advanced experience with DAX queries and data visualization.
• SQL: Proficient in querying, joining, and transforming data across relational databases.

✅ 2. Data Quality & Validation

Core Skills:

• Conducting data quality assurance and validation.
• Data cleaning, structuring, and linkage across systems.

Tools & Technologies:

• JMP
• Machine Learning: Experience applying ML techniques for data validation or enhancement.

🤖 3. AI Tools & Automation

Core Skills:

• Experience as a Prompt Engineer and in building intelligent agents.
• Ability to apply AI tools to solve real-world problems.

Tools & Technologies:

• OpenAI Library
• Microsoft AI Labs

🛠️ 4. Capability Development & Automation

Core Skills:

• Quick learner with the ability to adopt and apply new methods.
• Skilled in automating processes and building tools or apps.

Tools & Technologies:

• Python: Strong scripting and automation capabilities.
• MATLAB: Basic awareness and ability to apply for analytical tasks.
• You have a relevant technical degree and high level of data manipulation skills using applications such as SQL, PowerBI, Power Apps, Excel.

Core Skills

• Communication: You have a proactive mindset, passionate about engaging with end users, are a strong team player with excellent communication skills. You can understand how to share insights with stakeholders.
• Data management: You have a passion for data and an eye for detail with a proven track record in the ability to manipulate complex data sets and link different data sets. You can understand data sources, data organisation and storage.
• Data quality assurance, validation and linkage: You can conduct data quality assurance, data cleaning, validation and linkage. 
• Data visualisation: You can interpret requirements and present data in a clear and compelling way, summarise and present data and conclusions in the most appropriate format for users.
• Statistical methods and data analysis: You can demonstrate knowledge of statistical methodologies and data analysis techniques.
• Business Acumen: You have a good appreciation for the potential application of data analytics across different areas of the end-to-end R&D process. Deep knowledge of cross-functional data would be a plus, e.g. supply chain (manufacturing), sustainable future, procurement, finance, consumer insight.

STANDARDS OF LEADERSHIP 

• Passio