At a Glance
- Tasks: Collaborate with a major UK grocery retailer to unlock value from data and insights.
- Company: Join NIQ, a leading consumer intelligence company with a focus on innovation.
- Benefits: Enjoy flexible working, career development, and access to industry-leading analytical tools.
- Other info: Work in a dynamic environment with opportunities for growth and collaboration.
- Why this job: Make a real impact by turning complex data into actionable insights for retailers.
- Qualifications: Experience in FMCG or retail analytics and strong stakeholder management skills.
The predicted salary is between 48000 - 57000 £ per year.
As an Analytic Consultant in the Retail Customer Success team, you will work collaboratively with a major UK grocery retailer, acting as a trusted advisor and strategic partner. Your focus will be on helping the retailer unlock greater value from data, analytics and insights, turning complex market and shopper information into clear business actions and long-term growth opportunities. This is a highly collaborative, hands-on role.
You will work closely with retailer stakeholders and NIQ teams, combining Scanning, Panel and other datasets to ensure insight is consistently clear, relevant, and impactful. Working alongside the Customer Success Team Lead, you will play a key role in shaping the retailer relationship, identifying opportunities to deepen engagement, and supporting the strategic development of the account.
While the Team Lead is responsible for team leadership and delivery excellence, you will focus on retailer partnership, strategic consulting, thought leadership and driving insight-led growth. You will be expected to build trusted relationships across the retailer organisation, uncover opportunities where NIQ can create additional value, and help ensure that insights are translated into meaningful business outcomes.
Key Responsibilities
- Strategic Retailer Partnership: Build and maintain strong relationships with key retailer stakeholders across insight, category, commercial and customer functions. Act as a trusted advisor, helping stakeholders understand market trends, shopper behaviour and category performance and develop a deep understanding of the retailer's priorities, strategic objectives and business challenges.
- Strategic Insights & Consultancy: Translate complex business questions into actionable insight programmes and strategic recommendations. Connect retailer performance, category trends, shopper behaviour and market dynamics to provide a holistic view of opportunities and risks.
- Account Development & Value Creation: Identify opportunities to increase the value NIQ delivers across the retailer organisation. Support the adoption of new data sources, tools and analytical capabilities.
- Insight Quality & Delivery: Ensure all analytical outputs are clear, accurate, commercially relevant and actionable. Support the development of robust analytical approaches to answer complex retailer business questions.
- Collaboration & Capability Building: Work closely with Customer Success, Commercial, Analytics, Product and Operations teams to deliver an integrated client experience.
Experience & Skills
- Proven experience in FMCG, retail, or market research analytics.
- Strong analytical capability, especially using Consumer Panel.
- Demonstrated ability to manage stakeholders and build trusted relationships.
- Strong commercial awareness and understanding of business drivers.
- Confident presenter with strong storytelling skills.
Key Behaviours
- Relationship Builder: Establishes trust and credibility with stakeholders and becomes a valued business partner.
- Insight-Led: Passionate about turning data into meaningful, actionable insight.
- Strategic Thinker: Connects market trends, shopper behaviour and retailer priorities to identify future opportunities.
- Hands-On & Accountable: Takes ownership while staying close to delivery.
- Commercially Minded: Focuses on impact and client outcomes.
- Collaborative Influencer: Builds strong relationships and brings people together.
What we Offer
We provide the most complete and trusted view of consumers and markets in 90 countries covering 90% of the world’s populations. Focusing on consumer-packaged goods manufacturers and retailers, we combine unparalleled datasets, pioneering technology, and the industry’s top talent to create insights that unlock innovation and redefine what’s possible.
This is a full-time role based in either London or Oxford offering a hybrid working mode combining working from home and client offices.
Additional Information
Our Benefits include a flexible working environment, volunteer time off, LinkedIn Learning, and Employee-Assistance-Program (EAP).
NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria.
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.
Our commitment to Diversity, Equity, and Inclusion: At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve.
Analytical Consultant – Retailer Customer Success Team in London employer: NIELSENIQ
NielsenIQ in Oxford is an exceptional employer, offering a dynamic work culture that prioritises flexibility and professional growth. As a Junior Insight Analyst, you'll have the unique opportunity to collaborate with industry giants like P&G and Coca-Cola, while receiving comprehensive training to enhance your analytical skills and client engagement. With a strong focus on data-driven decision making, NielsenIQ fosters an environment where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Analytical Consultant – Retailer Customer Success Team in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like NIELSENIQ!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Analytical Consultant – Retailer Customer Success Team at NIELSENIQ.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like NIELSENIQ.
✨Apply Directly through Our Website
When you find a suitable opening like Analytical Consultant – Retailer Customer Success Team at NIELSENIQ, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Analytical Consultant – Retailer Customer Success Team in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at NIELSENIQ, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at NIELSENIQ. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at NIELSENIQ
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at NIELSENIQ!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
