At a Glance
- Tasks: Deliver insights for a UK grocery retailer using data analysis and storytelling.
- Company: Join NielsenIQ, a leader in retail data and insights.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for growth.
- Other info: Collaborate with diverse teams in a dynamic work environment.
- Why this job: Make an impact by translating complex data into actionable recommendations.
- Qualifications: Analytical skills and a passion for retail trends are essential.
The predicted salary is between 29700 - 36300 £ per year.
Nielsen IQ is seeking a client-facing Analyst to deliver insights for a UK grocery retailer.
You will combine Scanning and Panel data, translate complex data into clear recommendations, and work with NIQ teams to drive value for the client partnership.
The role is full-time with hybrid working in London or Oxford.
You will build expertise in UK retail trends and contribute to data-driven decision making while collaborating across teams.
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Insight Strategist - Retail Data & Client Storytelling employer: NielsenIQ
NielsenIQ is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those passionate about retail data and client storytelling. With opportunities for professional growth and a hybrid working model in vibrant locations like London and Oxford, employees are empowered to develop their expertise in UK retail trends while making impactful contributions to client partnerships.
StudySmarter Expert Advice🤫
We think this is how you could land Insight Strategist - Retail Data & Client Storytelling
✨Get Involved in Data Science Meetups
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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.
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We think you need these skills to ace Insight Strategist - Retail Data & Client Storytelling
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.
