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For Companies At a Glance
- Tasks: Dive into customer behaviour and deliver insights to drive marketing success.
- Company: Join a global consumer platform with millions of users and exciting digital experiences.
- Benefits: Enjoy remote work flexibility and a competitive salary up to £75,000.
- Why this job: Be part of a growing analytics team that values innovation and collaboration.
- Qualifications: Strong background in customer analytics, data science, and advanced modelling required.
- Other info: Opportunity for career growth into leadership or specialised roles.
The predicted salary is between 45000 - 75000 £ per year.
A global consumer platform with a fast-growing digital presence and millions of active users worldwide. The business partners with hundreds of leading global brands across retail, technology, food delivery, and travel, offering exclusive digital experiences and offers to a highly engaged customer base. As part of ongoing growth across data and analytics, the Senior Insight Analyst will join a growing analytics function, working closely with commercial teams, data engineering, and data science to deliver actionable insights across customer behaviour, marketing performance, and strategic growth opportunities.
This is a hands-on analytical role combining customer analytics, data science, and strategic insight. You’ll take ownership across a blend of traditional customer analytics and more advanced statistical modelling projects, supporting fast feedback loops across marketing performance, churn, forecasting, and member engagement. The role offers scope to grow into either a strong individual contributor role or people leadership position as the function scales.
Key Responsibilities- Analyse customer behaviour across the platform to support commercial growth and marketing optimisation.
- Deliver pre- and post-campaign analysis, segmentation work, and ongoing performance tracking.
- Build and deploy statistical models such as linear regression, clustering, forecasting, and advanced A/B tests.
- Work closely with ML Engineers, commercial teams, and senior stakeholders to translate insight into business action.
- Support marketing measurement, frequency analysis, churn reduction and commercial opportunity assessment.
- Collaborate cross-functionally with data engineering, product, and commercial teams on high-impact projects.
- Present clear, actionable insight to both technical and non-technical stakeholders across the business.
- Strong experience in customer analytics, data science, or advanced analytical modelling.
- Hands-on experience using Python for statistical analysis and modelling.
- Advanced SQL skills for data extraction and manipulation.
- Experience applying statistical methods such as linear regression, KMM, forecasting models, and experimentation.
- Strong communication skills with the ability to simplify complex analysis for business audiences.
- Degree in Mathematics, Statistics, Economics or related quantitative field.
- Experience working with SageMaker or similar cloud-based ML platforms.
- Prior experience in subscription or membership-based consumer businesses.
- Exposure to marketing mix modelling or marketing analytics.
- 1st Stage: Introductory screen (background, motivation & fit).
- 2nd Stage: Take-home technical task.
- 3rd Stage: Technical interview.
- Final Stage: Panel presentation & stakeholder Q&A.
Send your CV to Mohammed Buhariwala at Harnham using the Apply link on this page or connect directly to find out more.
Senior insight analyst employer: LinkedIn
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior insight analyst
✨Tip Number 1
Familiarise yourself with the latest trends in customer analytics and data science. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews, showcasing your passion and knowledge.
✨Tip Number 2
Brush up on your Python and SQL skills, as these are essential for the role. Consider working on personal projects or contributing to open-source projects that involve statistical analysis to demonstrate your hands-on experience.
✨Tip Number 3
Prepare to discuss specific examples of how you've used statistical methods in previous roles. Be ready to explain your thought process and the impact your analyses had on business decisions, as this will be crucial during the technical interview.
✨Tip Number 4
Practice presenting complex data insights in a simplified manner. Since you'll need to communicate findings to both technical and non-technical stakeholders, being able to convey your insights clearly will set you apart from other candidates.
We think you need these skills to ace Senior insight analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in customer analytics, data science, and statistical modelling. Use specific examples that demonstrate your hands-on experience with Python and SQL.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analysis and how your skills align with the role. Mention your experience with statistical methods and your ability to communicate complex insights clearly.
Showcase Technical Skills: In your application, emphasise your proficiency in Python and SQL. If you have experience with cloud-based ML platforms like SageMaker, be sure to include that as well.
Prepare for the Interview Process: Familiarise yourself with the interview stages outlined in the job description. Be ready to discuss your background, complete a technical task, and present your findings clearly to both technical and non-technical stakeholders.
How to prepare for a job interview at LinkedIn
✨Showcase Your Analytical Skills
As a Senior Insight Analyst, you'll need to demonstrate your strong experience in customer analytics and data science. Be prepared to discuss specific projects where you've applied statistical methods and how they contributed to business outcomes.
✨Master the Technical Task
The second stage involves a take-home technical task. Make sure you allocate enough time to complete it thoroughly. Use Python and SQL effectively to showcase your analytical capabilities, and don't hesitate to explain your thought process in your submission.
✨Communicate Clearly
During the interviews, especially the panel presentation, focus on simplifying complex analyses for non-technical stakeholders. Practice explaining your insights in a way that highlights their business impact, as this is crucial for the role.
✨Prepare for Cross-Functional Collaboration
Since the role involves working closely with various teams, be ready to discuss your experience collaborating with data engineering, product, and commercial teams. Highlight any successful projects where teamwork led to actionable insights or improved performance.
