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’ll work closely with product, engineering, commercial, and operations teams to provide insights, build dashboards, and ensure data is accessible and actionable. You’ll 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, prioritize 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 #LI-Remote
- Social events and annual meet ups
