Data Specialist - Ingredients

Role & responsibilities

Recipe Creation & Validation: As a Data Specialist, your core responsibility will be to build and validate ingredient level recipes across countries and categories. Recipes are constructed based on a combination of scraped product data, regulatory knowledge, and taxonomy alignment. Understanding how to interpret and leverage scraped ingredient data effectively is key to success in this role. You will ensure the outputs are accurate, logically structured, and regionally appropriate factoring in differences in local regulations and formulations.

DSS QA: You will also play a significant role in Digital Share of Shelf (DSS) quality checksreviewing the coverage and reliability of scraped data, spotting anomalies, and ensuring the taxonomy is well structured. Close collaboration with DSS, taxonomy, and regional teams is essential, creating structured feedback loops that continuously enhance our datasets.

Global Data Validation: Global data validation will be a major focus. You’ll run consistency checks across countries and subcategories, identify and fix issues, and ensure comparability in our outputs. This includes managing incoming data queries, owning the feedback process, and ensuring timely resolution by liaising with researchers, the PM, and other stakeholders.

Process documentation: Working with the Project Manager, you will contribute to the documentation of data workflows, rules, and checks, ensuring repeatability and scalability. A continuous improvement mindset is key, and over time, you’ll help propose and implement solutions that use AI or automation to improve QA, speed, and data consistency.

Insight support: You will also support the development of insights by identifying emerging ingredient patterns or data trends, and be comfortable interacting with clients whether it’s responding to queries, supporting custom requests, or contributing to workshops and presentations.

Collaboration & Stakeholder Engagement

This is a highly collaborative role, requiring ongoing coordination with:

1. The Project Manager for planning, prioritization, and delivery

2. Foundation team for structure, quality, and integration of DSS

3. In country researchers for data accuracy and local nuance, as needed

4. Cross functional teams for feedback and automation opportunities

5. Global Industry Manager to support insight generation and respond to client needs

You will be expected to manage feedback loops across these teams and act as a bridge between raw data and client ready intelligence.

Required Skills & Experience

• Educational background in biotechnology, life sciences, food science, or a related field"
• Strong understanding of ingredients and their application in food, nutrition, or personal care products
• Excellent analytical and numerical skills with experience working on structured datasets
• Detail oriented and methodical in identifying data inconsistencies and ensuring quality
• Proficiency in Excel (including formulas, pivot tables); strong documentation skills
• Strong communication and collaboration skills across global teams
• Comfort engaging directly with clients and supporting custom insights

Preferred/Bonus Skills

• Familiarity with Power BI, Tableau, or similar tools for visualizing data
• Interest in AI, automation, and scaling quality assurance processes
• Experience with Python, SQL, R, or VBA for data handling or automation
• Exposure to web scraping, or taxonomy driven data models

What Success Looks Like

• Consistently accurate and well documented recipe and DSS data
• Effective collaboration and well managed feedback loops with internal teams
• Structured, timely resolution of data queries and validation issues
• Clear process documentation that supports team scaling
• Contributions to insight generation and a strong interface with clients
• Active participation in driving automation and process evolution using AI

Preferred candidate profile