Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Transformation Specialist

NielsenIQ
Norwich
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer (Databricks)

Data Engineer

Data Architect (Insurance Domain)

Senior Consultant - Data Quality, Integration & Governance

Senior Consultant - Data Quality, Integration & Governance

Senior Data Scientist

Job Description

Department: Data Strategy & Solutions (DSS) - Product - Label Insight 

Solution focus: UK retail 

Employees can work remotely within the UK

About the Team: 

We are a unique team of subject matter experts committed to conducting and applying industry research. The transformation team is responsible for structuring our data to fuel product attributes which enable our customers and partners to meet their business objectives. This team helps to simplify an extremely complicated world of product data into smart, industry-forward, and relevant data to power our company’s products and solutions. 

About the Role: 

The Data Transformation Analyst will help deliver best-in-class health, wellness, and consumer transparency programs to support grocery retail customers. The Data Transformation Analyst is detail-oriented, able to make fast, but thoughtful decisions around Label Insight data, regulations, and trends in the CPG and grocery industries. You can effectively convey ideas and information about our data and solutions in an organized manner, with tailored messages based on who the audience is. The Data Transformation Analyst is accountable and responsible of capabilities & limitations of specific solution(s), including managing timelines, deadlines, expansion efforts, sales support (when appropriate), client CI and ticketing process & resolution, roadmaps, documenting and articulating needs to Product.

Responsibilities: 

Build and maintain LI attribute-powered solutions, including custom attributes for clients.  Deep expertise in core supported solution to help drive enhancements around data quality, coverage, and expansion  Self-sufficient of initial triage of hurdles, root cause analysis, of client inquiries. Effectively communicate full client-facing pitch, offer realistic solutions as reactions to client problems.  Help lead the execution of industry research to gain an understanding of the business and market to translate this into customer-facing insights that will support the ideation and implementation of marketplace research  Audit, improve and develop internal database taxonomies

Qualifications: 

Bachelor’s Degree 3+ years' experience in the CPG industry either by working directly at a brand or retailer or via a third-party data or technology company, consulting firm, or agency.  Strong and polished customer-facing presentation skills with customer-centric values.  Proficiency with Microsoft Office tools (Excel, PowerPoint, Word, SharePoint)  Comfortable learning new technology platforms (Coding, BI tools, GitHub, etc.)  Detail-oriented with the desire and ability to pick up new skills quickly 

Additional Information

Our Benefits

Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP)

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit

Want to keep up with our latest updates?

Follow us on: | | | 

Our commitment to Diversity, Equity, and Inclusion

NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: 

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.