At a Glance
- Tasks: Own forecasting and reporting, analyse menu and production data, and build self-serve analytics tools.
- Company: Frive, a fast-growing meal kit subscription business focused on real nutrition.
- Benefits: Flexible work environment, opportunities for creativity, and a chance to make a real impact.
- Other info: Collaborative culture with room for experimentation and personal growth.
- Why this job: Join a mission-driven team redefining food and use your data skills to shape the future.
- Qualifications: Strong SQL skills, experience with BI tools, and a curious mindset.
The predicted salary is between 35000 - 42000 £ per year.
Frive – At Frive, we’re redefining what food should be – real, wholesome and made without artificial stuff, because your body deserves better than the ultra-processed products that flood supermarket shelves.
Our mission is simple: to fuel you with real nutrition that supports your health and vitality – not just for today, but for the long run.
About the Role
Frive is a fast-growing meal kit subscription business in London.
The Data Analyst will own the reporting and forecasting the business runs on each week.
The postholder will work alongside the Senior Data & Analytics Manager, who leads the team and owns Looker, while taking full ownership of forecasting and operational reporting.
This work feeds directly into what Frive cooks, what it buys, and what lands in customers' boxes each week.
Frive builds a lot of its own internal tools rather than waiting on engineering, so there is plenty of room to experiment with how problems get solved.
Key Responsibilities
- Forecasting & Reporting
- Own the weekly forecasting and cutoff process end to end.
- Maintain and extend automated data pipelines that keep reporting tables up to date.
- Menu, Production & Margin Analysis
- Support menu and production decisions with analysis of menu allocation, production variance, and meal-level margin.
- Run the analysis behind changes to the meal assignment algorithm, covering margin and efficiency impact.
- Data Infrastructure & Self-Serve Analytics
- Build and scale the Looker instance to support a self-serve analytics culture across the business.
- Identify, develop, and implement new approaches and processes across the business.
- Cross-Functional Collaboration & Communication
- Collaborate closely with teams such as Menu Planning, Procurement, Ops, and Finance.
- Communicate findings in a way that is simple, clear, and actionable.
- Candidate Profile
Experience & Credibility
- Writes solid SQL and is comfortable working with large datasets, debugging complex queries, and thinking about how data models fit together; this is the one skill the team can't be flexible on.
- Has used a BI tool like Looker or Tableau to build dashboards people actually use.
- Bonus: has built things beyond dashboards, such as a Streamlit app or a Python script, to solve a problem.
- Personal Attributes
- Comfortable with ambiguity and messy operational data.
- Curious about the business itself, not just the numbers; the best analysis here comes from understanding how the kitchen, the menu, and the supply chain actually work.
- Proactive and excited to shape how the business uses data.
- Doesn't need to tick every box on this list, or hold a specific degree; mindset, skills, and willingness to learn matter more.
- Competencies & Style
- Can explain analysis to people who don't work with data, in a way they can act on.
- Comfortable working in a fast-moving, collaborative team where things can change quickly.
- Knowledge & Skills
- Strong SQL skills, with the ability to debug complex queries and reason about data models.
- Practical experience with BI tools (e. g. Looker, Tableau) for dashboard-building.
- What Success Looks Like
- A weekly forecasting and cutoff process that runs smoothly and reliably.
- Menu, production, and margin analysis that directly informs what gets cooked and bought each week
- A scaled Looker instance supporting genuine self-serve analytics across the business.
- Clear, actionable findings that non-technical teams can act on with confidence.
- #J-18808-Ljbffr
Data Analyst employer: Frive
Frive is an exceptional employer that fosters a dynamic and creative work culture, perfect for those looking to make a significant impact in the digital space. With opportunities for personal and professional growth, employees are encouraged to innovate and collaborate closely with leadership, ensuring that every voice is heard. Located in the vibrant UK, Frive offers a unique chance to engage with diverse audiences while building a magnetic personal brand alongside the Founder and CEO.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨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 Frive.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst at Frive, 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 Data 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 Frive, 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 Frive. 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 Frive
✨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 Frive!
✨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.