> Markdown version of [/jobs/ext/4612355-senior-data-analyst](https://www.wearedevelopers.com/jobs/ext/4612355-senior-data-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Data Analyst

- **Company:** ZAVA
- **Location:** London, United Kingdom
- **Experience:** Expert
- **Salary:** £80,212
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Google AdWords, Artificial Intelligence, Big Data, BigQuery, Data Presentation, Data Visualization, Data Warehousing, EHealth, Google Analytics, Python (Programming Language), MySQL, Power BI, SQL Databases, Tableau (Software), Usage Analysis, Git, Data Analytics, Looker Analytics, Software Version Control, Amazon Redshift
- **Published:** November 7, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5956246860

## About the Role

* Exceptional analytical problem-solving skills, with a proven track record of prioritising effectively and thriving in fast-paced environments.
 * Experimentation and product analytics expertise. Experience with funnels, cohorts, experimentation and statistical inference, including the limits of observational data and how to communicate uncertainty.
 * Intermediate SQL experience. Confidence in writing efficient SQL queries on large-scale datasets in data warehouses (AWS Redshift, MySQL) with practical Python proficiency.
 * Experience in commercial analytics: acquisition, retention and customer lifetime value modeling.
 * Experience utilising AI-driven capabilities within modern BI tools (e.g., Tableau, Looker, Lightdash, Power BI) to streamline analytical workflows and extract actionable insights.
 * Understanding of e-commerce funnels & event tracking, event-level data,
 * Prioritise competing requests based on impact and effort, and confidently push back to stakeholders, with evidence and clear trade-offs, when a request isn't the best use of the team's time.
 * Ability to structure messy problems, separate drivers from noise, and know when more precision isn't worth the time.
 * Ownership and influence: Independently lead important analyses, build relationships with senior stakeholders, and challenge the prevailing view when needed.
 * Systems mindset: Spot patterns in repeated requests and create durable solutions, with semantic metrics, BI or data modelling experience valued.
 * A self-learner who is flexible and open to change.
 * Ship and learn quickly: Deliver useful intermediate answers early, make uncertainty visible, seek feedback and iterate rather than wait for a polished one-off analysis.
 * Raise the analytical bar: Review others' work constructively, share methods openly, and question weak conclusions.
 * Supporting the wider business by helping to define meaningful, relevant and easily understood KPIs around product performance
 * Inspiring others to love and use data through effective storytelling
 * Presenting insights and opportunities in a clear manner such that product design is based on objective evidence wherever possible
 * Demonstrate faster learning cycles through early delivery, iteration and thoughtful use of AI tools

Nice to have, but not at all essential

 * Working with modern data stacks, for example, BigQuery, AWS Redshift, dbt, Looker, Tableau, Lightdash, MCP
 * Working with events/web tracking tools (Segment/Google Analytics)
 * Experience with marketing (AdWords, Paid Search, etc.), product or operational analytics
 * Experience with version control (we use Git)
 * Healthcare or digital healthcare experience

## Description

The rapidly expanding digital healthcare industry presents a dynamic and highly competitive landscape.

In this role, the Senior Data Analyst will collaborate directly with key business partners to solve complex problems, deliver actionable insights, and champion data-driven strategic planning.

We are seeking a proactive Senior Data Analyst to empower leadership with deeper performance visibility, sharper decision-making, and accelerated learning cycles. Partnering closely with leaders across Growth, Product, Operations, and Finance, you will end-to-end own core commercial opportunities, from framing questions and diagnosing root causes to framing recommendations and tracking business impact.

Beyond traditional reporting, we need a curious problem-solver who uncovers changing trends, determines underlying drivers, and guides organisational action. You will transform ad-hoc inquiries into scalable, repeatable analytical solutions, advancing our transition toward automated diagnosis, real-time monitoring, and dependable self-service analytics. While focusing on UK business priorities, you will also partner with international analytics peers across the Hims & Hers Group.
What you'll own

 * Lead Product Analytics: Evaluate product funnels and the patient journey through a standardised, systematic framework driven by evidence-based insights. Own product and funnel analytics end to end, partnering with product leadership to set quarterly priorities and turn patient journey insight into sized opportunities, tracking standards and clear recommendations.
 * Experimentation. Own the A/B testing framework and programme (standards, prioritisation, SiteSpect management), acting as the business's go-to authority on experimentation. Lead cross-functional sessions that share results and learnings, and continuously improve the process.
 * Diagnose product performance with commercial impact: Deeply analyse user funnels, feature adoption, and retention cohorts to uncover core drivers of business growth. Translate complex behavioural data into clear commercial insights, identifying high-leverage opportunities to optimise monetisation and user experience.
 * Drive decisions: Work backwards from commercial objectives, challenge assumptions, recommend concrete actions with trade-offs, and follow up to check whether the decision worked.
 * Measure impact: Design and evaluate experiments, launches and operational changes, using cohort analysis and causal methods to make credible claims even when evidence is incomplete.
 * Build repeatable capabilities: Turn frequent investigations into trusted metrics, models, monitoring, automated diagnostic workflows, AI skill writing, and self-service tools, with shared definitions across markets.
 * Work AI-natively: Use AI and modern BI tools to create dashboards, visualisations, and automated workflows that bring key metrics to life, accelerating exploration and repetitive investigation while maintaining full ownership of data accuracy and underlying assumptions.
 * Become a trusted analytical partner to stakeholders, independently owning material commercial questions and improving the reliability and usability of core metrics, models and analytical workflows