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- Tasks: Analyse data to uncover trends and insights, building dashboards for impactful decision-making.
- Company: Join a dynamic Data & Analytics team at a forward-thinking company.
- Benefits: Enjoy 30 days holiday, fully remote work, and flexible hours.
- Why this job: Make a real impact by turning data into actionable insights and driving innovation.
- Qualifications: 2-4 years in data analytics, strong SQL skills, and a passion for AI.
- Other info: Collaborative environment with opportunities for professional growth and social events.
The predicted salary is between 28800 - 43200 £ per year.
We are seeking a Data Analyst to join our growing Data & Analytics team—the powerhouse behind data-driven decision making across the company. In this role, you will work closely with product, engineering, commercial, and operations teams to provide insights, build dashboards, and ensure data is accessible and actionable. You will help design experiments, measure outcomes, and contribute to AI and internal productivity initiatives, making data a true competitive advantage for the organisation.
Key Responsibilities
- Analysis and insights
- Conduct deep-dive analyses to identify trends, opportunities, and risks across product, customer, and business data.
- Support strategic decisions by providing actionable insights to product, engineering, commercial, and operations teams.
- Partner with stakeholders to define metrics, KPIs, and reporting needs.
- Reporting and visualization
- Build and maintain dashboards and reports in Power BI (and potential other BI tools).
- Create clear and compelling data visualizations that make insights accessible to non-technical stakeholders.
- Ensure consistent definitions, documentation, and data integrity across reporting.
- Experimentation and measurement
- Assist in designing and analyzing A/B tests and experiments to evaluate product and business initiatives.
- Track and measure the impact of AI-powered features and internal productivity tools.
- Data accessibility and enablement
- Enable self-service analytics by developing standardized datasets, dashboards, and documentation.
- Promote data literacy across teams through training and knowledge-sharing.
- Collaboration and support
- Proven ability to work within a structured request system, prioritise competing requests, clearly communicate timelines, and collaborate with stakeholders to clarify the objective behind each data request.
- Work closely with engineering to ensure reliable, clean, and well-structured data pipelines.
- Support the Data Science & Analytics Manager in delivering cross-company data initiatives.
Requirements
- Experience levels
- 2-4 years in data/analytics, with exposure to data engineering or ML workflows.
- Strong proficiency in SQL and Excel.
- Has worked in a small or scaling company.
- Has influenced senior stakeholders using data.
- Evidence of owning projects end-to-end rather than only executing tasks.
- Desirable, but not required:
- Prior experience in SaaS, EdTech, or B2C/B2B2C environments.
- Experience working with modern data platforms (Snowflake, BigQuery, Databricks).
- Experience with Python.
- Interest in AI and how analytics can support emerging technologies.
- Skillset (including transferables)
- SQL at an advanced level, comfortable writing transformations and optimising queries.
- Experience with a modern analytics stack (DBT, cloud warehouse, BI tool).
- Ability to translate ambiguous business questions into structured analysis.
- Strong written communication in a remote-first team.
- Basic data engineering principles (pipelines, version control, testing).
- Commercial awareness — understands metrics like LTV, CAC, churn.
- Stakeholder management and ability to influence without authority.
- Experimentation mindset — understands A/B testing, causal thinking, and KPI development.
- Clear storytelling with data.
- Transferable skills: problem structuring, prioritisation, systems thinking, ability to learn new tools quickly.
- Professional memberships
- Desirable, but not required: Published articles, blogs, talks, or teaching.
- Mentorship involvement (mentor or mentee).
- Qualifications & additional certifications
- Strong quantitative background (STEM degree or equivalent practical experience).
- Also desirable, but not required: Certification in a cloud platform (Azure, AWS, GCP).
- Certification in Power BI, Tableau, or similar.
- Data Build Tool fundamentals or equivalent.
Benefits
- 30 days' holiday per year (inclusive of UK bank holidays).
- 100% remote & flexible working.
- Social events and annual meet ups.
Data Analyst (Mid Level) in London employer: Dataanalystjobs
Contact Detail:
Dataanalystjobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst (Mid Level) in London
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio of your best data visualisations and analyses. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data-related questions. Think about how you’d explain complex concepts simply, as you’ll need to communicate with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s the best way to ensure your application gets noticed!
We think you need these skills to ace Data Analyst (Mid Level) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Analyst role. Highlight your experience with SQL, Excel, and any relevant projects you've owned from start to finish. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data and how your skills align with our mission at StudySmarter. Don't forget to mention any experience with A/B testing or data visualisation tools.
Showcase Your Analytical Skills: In your application, include examples of how you've used data to influence decisions or solve problems. We love seeing clear storytelling with data, so make sure to highlight your analytical mindset and any relevant metrics you've worked with.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you'll be one step closer to joining our awesome Data & Analytics team!
How to prepare for a job interview at Dataanalystjobs
✨Know Your Data Tools
Make sure you’re familiar with the tools mentioned in the job description, especially SQL and Power BI. Brush up on your skills and be ready to discuss how you've used these tools in past projects. Being able to demonstrate your proficiency will show that you're a strong candidate.
✨Prepare for Scenario Questions
Expect questions that ask you to solve real-world problems or analyse data scenarios. Think about how you would approach A/B testing or how you’ve influenced stakeholders with data insights in the past. Practising these scenarios can help you articulate your thought process clearly.
✨Showcase Your Collaboration Skills
Since this role involves working closely with various teams, be prepared to discuss your experience collaborating with different stakeholders. Share specific examples of how you’ve communicated complex data insights to non-technical audiences and how you’ve prioritised competing requests.
✨Demonstrate Your Experimentation Mindset
Highlight your understanding of experimentation and measurement. Be ready to talk about any A/B tests you've designed or analysed, and how you tracked their outcomes. This will show that you not only understand the theory but have practical experience applying it.