Senior Product Analyst, Numan

• At least 2 years of experience in a high-growth tech environment, ideally within product analytics
• Strong SQL skills – you’ll be using SQL daily
• Python proficiency and experience working with experimentation frameworks
• The ability to communicate complex technical insights clearly to non-technical stakeholders
• A track record of conducting impactful analyses that drive business metrics, such as improving user retention or acquisition
• Using data analytics tools to analyse large datasets and derive actionable insights
• Designing, implementing, and generating multi-stakeholder dashboards
• A strong growth mindset and business intuition, ideally within a digital consumer environment
• Working independently and focusing on pragmatic solutions with high impact
• Knowledge of statistical methods (e.g., regression, clustering, segmentation)
• Understanding of software development best practices (e.g., Git)

Desirable

• Reporting to the Head of Product Analytics & Data Science, you will own product analytics and experimentation within the Men’s Health Business Unit
• You will be responsible for identifying impactful, high-leverage areas of work to advance the Men’s Health proposition at Numan
• Collaborating closely with a cross-functional team that includes a product manager, engineers, product designers, and a commercial manager, you will spearhead analytical discovery of patient trends and interactions
• You will empower the team to run and analyse numerous product experiments, becoming an essential decision-maker within the team
• Joining a nascent product analytics and data science team, you will have the opportunity to shape the future of product analytics and data science at Numan
• Leading product analytics and experimentation within the Men’s Health Business Unit
• Identifying high-impact areas for analytical discovery and experimentation
• Collaborating with cross-functional teams to analyse patient trends and interactions
• Running and analysing multiple product experiments to support business decisions
• Defining and implementing best practices within the analytics and data science function