Data Analyst (Healthcare)

Location: London, United Kingdom; hybrid with 3 days per week in the office

Company

hirify.global is a fast-growing healthtech scale-up building an all-in-one healthcare platform for diagnosis, treatment, and ongoing patient support.

What you will do

• Conduct ad-hoc analyses across Operations, Finance, Clinical, and Programme teams.
• Identify trends, patterns, and anomalies in operational and clinical data affecting service delivery and patient outcomes.
• Design and maintain Looker dashboards covering programme delivery KPIs, financial performance, and other business metrics.
• Develop automated reports and ensure dashboards are accurate, performant, and easy to navigate.
• Write optimized SQL and collaborate with Data Engineering on data modelling, dbt transformations, governance, and data quality.
• Communicate analytical findings clearly and promote self-serve, data-driven decision-making across the organisation.

Requirements

• 2–4 years of experience in data analysis, business analysis, or a similar analytics role.
• Strong SQL skills, including querying, filtering, joining, and aggregating data.
• Experience with at least one BI or data visualization tool, such as Looker, Tableau, or Power BI.
• Familiarity with modern data stack tools such as BigQuery, Snowflake, PostgreSQL, or dbt.
• Strong analytical, problem-solving, communication, and stakeholder collaboration skills.
• Availability to work from the London office 3 days per week is required.

Nice to have

• Degree in Statistics, Mathematics, Computer Science, Economics, or another quantitative subject.
• Experience in healthcare, public health, or regulated industries.
• Exposure to Python or R for data analysis and statistical work.
• Experience in fast-growing, high-impact environments.
• Familiarity with dbt or other data transformation frameworks.

Culture & Benefits

• Work in a fast-paced healthtech environment with more than 1 million members.
• Contribute to a healthcare platform focused on improving patient outcomes at scale.
• Collaborate with technical and non-technical stakeholders across multiple business functions.
• Support smarter, data-informed decisions and self-serve analytics across the organisation.