data analyst in healthcare

VOY is a healthtech scale-up building an all-in-one healthcare platform that helps users diagnose possible conditions, access treatment, and receive ongoing support. The company delivers personalised care across weight loss, menopause, hair loss, and TRT to over 1 million members across the UK, Germany, and Brazil.

• Conduct ad-hoc analyses to answer business questions from Operations, Finance, Clinical, and Programme teams;
• Identify trends, patterns, and anomalies in operational and clinical data that impact service delivery and patient outcomes;
• Present findings in clear, compelling ways that drive decision-making across the organisation;
• Design and build Looker dashboards tracking key business metrics, including programme delivery KPIs and financial performance;
• Develop automated reports that keep stakeholders informed without manual updates;
• Ensure dashboards are accurate, performant, and easy to navigate;
• Write clear, optimised SQL to query and manipulate data reliably;
• Collaborate with the Data Engineering team on data modelling, dbt transformations, and data governance;
• Identify and escalate data quality issues and help ensure consistency across systems;
• Help define and track important metrics, ensuring every KPI is understood and correctly calculated;
• Work with Operations, Clinical, Finance, and Programme Delivery stakeholders to understand their data needs;
• Communicate complex data concepts accessibly to non-technical stakeholders;
• Help drive adoption of data-driven thinking and self-serve analytics across the organisation.

• 2–4 Years of experience in a data analyst, business analyst, or similar analytics role;
• Proficiency in SQL, including exploring, filtering, joining, and aggregating data;
• Experience with at least one BI or visualisation tool, such as Looker, Tableau, or Power BI;
• Strong analytical and problem-solving skills with attention to detail;
• Excellent communication skills and the ability to explain complex findings clearly to diverse audiences;
• Nice to have: A degree in Statistics, Mathematics, Computer Science, Economics, or another quantitative subject; experience in healthcare, public health, or regulated industries; Python or R for data analysis and statistical work; experience in fast-growing, high-impact environments; familiarity with modern data stacks and tools such as BigQuery, Snowflake, PostgreSQL, dbt, or other data transformation frameworks.

• Hybrid role requiring 3 days per week in the office.