At a Glance
- Tasks: Deliver market insights and manage analytical projects for top drinks companies.
- Company: NielsenIQ, a leader in market intelligence based in Stockport.
- Benefits: Flexible work environment and opportunities to enhance client success.
- Other info: Collaborative culture with a focus on delivering high-quality results.
- Why this job: Make a real impact by interpreting data and driving revenue opportunities.
- Qualifications: Proficiency in Excel and Power BI, with strong analytical skills.
The predicted salary is between 30000 - 40000 £ per year.
NielsenIQ in Stockport is seeking a Data and Insights Analyst to deliver essential market insights for leading drinks companies. This role encompasses project management of analytical services and involves close collaboration with commercial teams to enhance revenue opportunities.
The ideal candidate will excel in analytical tools such as Excel and Power BI, capable of interpreting data and client briefs while ensuring high-quality deliverables. A flexible work environment and the chance to contribute significantly to client success are key features of this role.
Data & Insights Analyst — Market Intelligence & Client Delivery in Manchester employer: NIELSENIQ
NielsenIQ in Stockport is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. Employees benefit from flexible working arrangements, comprehensive professional development opportunities, and the chance to make a meaningful impact on leading drinks companies through insightful data analysis. Join us to be part of a team that values your contributions and supports your growth in a thriving market intelligence environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data & Insights Analyst — Market Intelligence & Client Delivery in Manchester
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We think you need these skills to ace Data & Insights Analyst — Market Intelligence & Client Delivery in Manchester
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!
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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!
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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
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✨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.
