Data Analyst (London, UK)

This is a Full-Time Role (40 hours per week, 5DWW) with no option for part-time work. While this is a remote-first opportunity, the candidate filling this role must be a resident of the Netherlands or in the U.K. at the start of employment. Additionally, they must be within commuting distance of our office in Amsterdam or London. 
Please visit our Careers page to review all opportunities and submit your application for the role(s) that best fit your location and work authorization.

About the Team

The Data & AI team is responsible for building B Lab's data platform, delivering on business priorities, and scaling AI adoption across the organization. The team reports directly to the CTDO. Organizational Objectives is one of three pillars within Data Analytics & AI Enablement — the demand-side of the Data & AI team. It turns trusted data into decisions on B Lab's most important organizational objectives, working alongside business and programme owners across the network. This Data Analyst role provides broad, cross-topic analytical support within the pillar and, as needed, across the wider team.

About the Opportunity

The Data Analyst is a broad, cross-topic analyst within the demand-side of the Data & AI team. Working under the direction of the Director of Data Analytics & AI, the role builds dashboards, prepares reports, and runs analyses across a wide range of topics — from growth to comms and standards/impact — and is the responsive for various requests coming from the Organization Objective working groups (NPs). This is a developing role: the analyst contributes ideas and acts as a thought partner where they can, while working with guidance and review from the Director and senior analysts. Alongside day-to-day analysis and requests, the role helps make data easier to use for staff across the organisation — building reusable, well-documented, global assets — and grows toward a more independent, specialised analyst over time.

Core Responsibilities 

Data Requests & Stakeholder Support (40%)

• Run the day-to-day data-requests intake related to Organizations Objective
• Participate as a thought partner in some Organization Objective workstreams, providing proactive ideas about the role of data in the workstream
• Speak with staff across the organisation to understand their data needs and translate them into clear analyses, reports, or dashboard updates.
• Act as a responsive, helpful first point of contact for data questions across topics (growth, comms, policy, and more), escalating or seeking guidance on more complex requests.

Dashboards, Reporting & Analysis (35%)

• Build, upgrade, and maintain dashboards across a range of topics, from certification and growth to comms and standards/impact.
• Prepare recurring and ad-hoc reports, and conduct data analysis to surface trends and answer questions for teams.
• Collaborate with the platform team (data engineers / analytics engineer) to keep dashboards accurate as data sources and schemas change.
• Apply basic statistical methods and clear data storytelling to make findings understandable and useful.

Data Enablement, Accessibility & Learning (25%)

• Help make data easier to use for staff across the organisation — building reusable, well-documented assets (guides, templates, self-serve dashboards) designed for the whole global network, not a single team.
• Support the development and upkeep of internal data-use guidance and light training materials, distilling complex data into digestible, shareable formats.
• Grow their own capability — learning from senior analysts, participating in team practices (retrospectives, feedback), and building toward a thought-partner role over time.

About You

• Relevant degree (Mathematics, Computer Science, Information Management, Statistics, or comparable)
• A minimum of 1–2 years of relevant experience focused on data analytics
• Strong analytical skills: the ability to collect, organise, analyse, and communicate information with attention to detail, presentation, and accuracy
• Clear communication and data storytelling: the ability to apply and explain basic statistical methods (e.g. descriptive statistics and hypothesis testing) in decision-making
• Proficiency with Business Intelligence tools (Tableau, Power BI, Metabase, or similar) and querying databases (PostgreSQL, AWS Athena, or similar)
• Programming and data tools: SQL (mandatory); R or Python preferred; Excel / Google Sheets