At a Glance
- Tasks: Analyse customer behaviour and performance to deliver impactful insights.
- Company: Join a dynamic team at a leading analytics firm focused on retail and media.
- Benefits: Enjoy flexible working, competitive salary, and comprehensive health benefits.
- Other info: Collaborative culture with opportunities for professional growth and exciting company events.
- Why this job: Make a real difference by translating data into actionable insights for retailers.
- Qualifications: 2-4 years in analytics with strong SQL and Excel skills required.
The predicted salary is between 35000 - 45000 £ per year.
The Insight Analyst is accountable for delivering high-quality, sector-aligned analytics that deepen understanding of customer behaviour, retailer performance, and media effectiveness. Aligned to a defined industry sector, this role applies structured analytical frameworks to interpret how customers engage, spend, and respond to media and loyalty activity. The Insight Analyst translates behavioural data into commercially meaningful insight that supports retailer growth and performance marketing optimisation. This role is critical in ensuring scalable, accurate analytics delivery while developing expertise in customer intelligence and revenue drivers within the sector.
Responsibilities
- Customer Behaviour & Performance Analytics: Analyse customer engagement, transaction, and behavioural data within an assigned sector. Identify patterns in spend, frequency, retention, and campaign response. Support understanding of how loyalty mechanics and media activity influence behaviour. Contribute to performance evaluations that explain not just “what happened” but “why.”
- Revenue & Performance Support: Analyse performance drivers, trends, and risks within the market. Support revenue tracking and variance identification. Escalate data inconsistencies or performance concerns appropriately. Apply established measurement frameworks consistently across the sector.
- Insight Development & Commercial Application: Translate analytical outputs into clear, commercially meaningful narratives. Contribute to retailer-facing presentations and market updates. Support development of thought leadership. Identify repeat analysis that can be standardised or improved.
- Data & Methodology: Maintain data accuracy and integrity across outputs. Use SQL and BI tools to extract and structure data effectively. Apply defined methodological standards set by the Head of Commerce Media Insight. Continuously develop technical and analytical capability.
What Good Looks Like
- Reliable, high-quality outputs with minimal rework.
- Strong understanding of market performance drivers.
- Increasing confidence in explaining commercial implications.
- Growing independence and ownership of local insight delivery.
Requirements
- Experience: 2–4 years’ experience in analytics, insights, or commercial data roles. Experience in retail, loyalty, media, or customer analytics preferred.
- Technical Capability: SQL (Essential) writing and troubleshooting queries involving complex joins, functions, aggregations, subqueries etc. Excel (Essential) creating and adapting spreadsheet models including complex formulae, charts, pivots, array functions, lookups etc. Familiarity with BI tools (Tableau, Power BI, Looker). PowerPoint (Essential) created and adapting high quality presentations and reports for internal and external audiences. Comfortable handling large datasets and structured reporting outputs.
- Analytical & Commercial Capability: Strong attention to detail and structured thinking. Ability to translate data into clear commercial insight. Growing understanding of media effectiveness and revenue drivers. Curious, proactive, and commercially aware. Works effectively across time zones with UK-based teams. Escalates issues early and constructively. Demonstrates accountability and reliability.
Flexible working options: we are operating a hybrid working model with 3 days a week from the office. Pension: Hargreaves Lansdown – 6% matched contribution. Generous family friendly cover. Income protection. Critical illness cover. Life insurance cover. Optical cover. Yulife app for access to employee wellbeing and discounts. Perks at Work, cashback/discount shopping site. Salary sacrifice program which includes cycle to work scheme, electric car scheme and season ticket loans. Company events i.e. Christmas party, all-company event and other social/hosted events during the year (we have an active social committee!).
Insights Analyst employer: Reward
Reward is an exceptional employer that prioritises innovation and employee development within the dynamic field of customer engagement. With a strong commitment to work-life balance, flexible working arrangements, and a supportive culture, employees are empowered to thrive while contributing to meaningful client solutions. The company also offers competitive benefits, including pension contributions and family-friendly policies, making it an attractive place for professionals seeking growth and impact in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Insights Analyst
✨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 Reward!
✨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 Insights Analyst at Reward.
✨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 Reward.
✨Apply Directly through Our Website
When you find a suitable opening like Insights Analyst at Reward, 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 Insights Analyst
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 Reward, 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 Reward. 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 Reward
✨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 Reward!
✨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.
