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For Companies At a Glance
- Tasks: Analyze data and collaborate on market research projects to drive brand insights.
- Company: Join a leading, employee-owned market research company with a B-Corp certification.
- Benefits: Enjoy a collaborative work environment and opportunities for skill development.
- Why this job: Make a real impact in brand strategy while working with top industry names.
- Qualifications: Strong R programming skills and proficiency in Excel are essential; curiosity is key!
- Other info: Experience with advanced analytical techniques is a plus; join a supportive team!
The predicted salary is between 28800 - 48000 £ per year.
Data Analyst – Join a Growing Market Research Powerhouse
Are you a data-driven individual with a passion for brands and advertising? Do you thrive in a collaborative environment where your analytical skills can make a real impact? If so, we want to hear from you!
We are a leading market research company known for our cutting-edge data analytics and deep understanding of brand strategy, experience, and communications. We partner with some of the biggest names in the FMCG, financial, automotive, leisure, and healthcare sectors, helping them grow and “glow” through insightful research. We’re proudly employee-owned, a certified B-Corp and Investors in People Gold.
As a Data Analyst, you will play a crucial role in our project lifecycle, from initial design to final delivery. You’ll work alongside a close-knit team of experienced researchers and analysts, contributing to both data-focused projects and those leveraging survey data across a diverse range of brands. This role offers the opportunity to develop your analytical skills, working with techniques like segmentation and driver analysis, and progress from standard marketing techniques to more advanced analytical methods.
Responsibilities:
- Collaborate with senior team members to design market research projects with an analytical focus (e.g., driver analysis, segmentation, conjoint).
- Clean and analyze survey data, performing tasks ranging from creating simple tables to conducting complex explorations.
- Work effectively within a team environment, contributing to the overall success of the company.
- Communicate confidently and clearly with both colleagues and clients.
Essential Skills:
- Strong proficiency in R programming (e.g., data wrangling, function writing, string processing). Knowledge of other statistical packages (e.g., SPSS) is a plus.
- Expertise in MS Excel and comfort with MS PowerPoint.
- Meticulous attention to detail and a systematic approach to coding.
- A curious mindset, with the ability to understand client questions and anticipate their needs.
- A talent for uncovering stories within data and translating them into actionable insights.
Desirable Skills:
- Experience with analytical techniques in primary research, including:
- Regression techniques (linear, logistic, Shapley).
- Segmentation.
- MaxDiff/Conjoint.
- Pricing techniques (Van Westerndorp, Gabor-Grainger).
- Familiarity with MS Excel Macros or VBA.
- Knowledge of dashboarding packages (e.g., Shiny, Dash, PowerBI, Tableau).
- Working knowledge of Linux OS.
We Are Aspire Ltd are a committed employer.
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Data Analyst employer: TieTalent
Contact Detail:
TieTalent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarize yourself with R programming and its applications in data analysis. Since strong proficiency in R is essential for this role, consider working on personal projects or contributing to open-source projects that showcase your skills.
✨Tip Number 2
Network with professionals in the market research field. Attend industry events or webinars where you can meet potential colleagues and learn more about the latest trends and techniques in data analysis.
✨Tip Number 3
Prepare to discuss your analytical approach during interviews. Be ready to share examples of how you've tackled complex data problems and the insights you've derived from your analyses.
✨Tip Number 4
Showcase your ability to communicate data insights clearly. Practice explaining your findings to non-technical audiences, as effective communication is key in collaborating with both colleagues and clients.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your proficiency in R programming and any experience with statistical packages like SPSS. Emphasize your analytical skills and any relevant projects you've worked on that demonstrate your ability to clean and analyze survey data.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data analysis and market research. Mention specific techniques you are familiar with, such as segmentation or regression analysis, and how they relate to the role. Show enthusiasm for working in a collaborative environment.
Showcase Your Analytical Mindset: During the application process, highlight your curiosity and ability to uncover stories within data. Provide examples of how you've translated data insights into actionable recommendations in previous roles or projects.
Prepare for Potential Assessments: Be ready for potential assessments or tests that may evaluate your analytical skills and proficiency in R programming. Brush up on your coding skills and be prepared to demonstrate your problem-solving abilities with real data scenarios.
How to prepare for a job interview at TieTalent
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data analysis techniques, especially in R programming. Highlight specific projects where you've used segmentation or driver analysis to derive insights.
✨Demonstrate Team Collaboration
Since the role emphasizes teamwork, share examples of how you've successfully collaborated with others on data-focused projects. Discuss your approach to working within a team and how you contribute to collective success.
✨Communicate Clearly
Practice articulating complex data findings in a clear and concise manner. Be ready to explain how you would communicate insights to both colleagues and clients, ensuring they understand the implications of the data.
✨Prepare for Technical Questions
Expect questions related to statistical packages and analytical techniques. Brush up on your knowledge of SPSS, Excel, and any other relevant tools, and be ready to discuss how you've applied them in past roles.
