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Salary: GBP 80,000 - 110,000 / annual
Fresha is the leading AI-powered operating system for the global beauty and wellness industry. In May 2026, the company secured an $80M growth investment from KKR at a $1B valuation, reaching unicorn status with $285M in total funding. Already profitable, Fresha operates at global scale with 130,000+ beauty and wellness businesses across 120 countries and 1.5+ billion appointments booked to date.
You will be the Principal Analyst for Fresha's Commercial function, owning analytics across Direct Sales, Account Management, and Customer Experience/Partner Support. Reporting to the Head of Analytics with technical leadership responsibilities (no people management), you'll be the day-to-day technical partner to Commercial leadership, trusted to challenge stakeholder thinking when data points elsewhere.
Key responsibilities include: designing decision-support systems that surface opportunities and risks for Account Management and CRM teams; owning analytics for the entire Commercial function including Direct Sales performance, retention, and customer success operations; building and maintaining unit economics models for the commercial engine (acquisition cost, lifetime value, margin, compensation impact); designing and evolving compensation and incentive structures for Direct Sales and Account Management; owning forecasting for retention, churn, revenue growth, and customer success metrics; building predictive models (e.g., churn risk scoring) that materially improve team prioritization; designing and running statistically rigorous experiments on compensation, pricing, or retention interventions; driving automation of customer support insight generation using modern data and AI tooling; and managing day-to-day task and priority management for the Commercial analytics pod.
You'll work with significant autonomy, owning forecasting and unit economics end-to-end, setting the technical bar for other analysts, and tackling the pod's hardest, most ambiguous problems with minimal oversight. This is a senior individual contributor role emphasizing technical leadership and strategic partnership with the business rather than people management.
Fresha's Analytics function operates around three principles: understand what's really going on (not just report the requested number); partner with the business rather than simply serve it; and raise what matters before being asked. The role requires someone who thinks like an operator, thrives in fast-paced environments, and wants to make significant impact on how a fast-growing commercial engine runs.
Location: The Bower, 207-211 Old Street, Tower, London EC1V 9NR. Four days in office, Wednesdays remote.
REQUIREMENTS:
- 6-10 years in a senior analytical role with strong commercial analytics, finance, FP&A, or retention analytics background (ideally B2B SaaS or marketplace experience)
- Deep experience in forecasting, unit economics, and pricing analysis with a track record of models that held up under real business decisions
- Comfortable analysing or advising on compensation and incentive structures—not just reporting on sales performance after the fact
- Strong SQL and Python skills used daily for analysis, with hands-on experience contributing to dbt models and working in GitHub-based workflows
- Experience with modern data stack (Snowflake and dbt); internal BI tool is Python-based (Plotly), though experience with any modern BI tool acceptable
- Track record of being the trusted analytical partner to commercial leadership—shaping strategy, not just measuring it after the fact
- Comfortable challenging stakeholders, including senior ones, when data doesn't support proposed direction
- Fluent use of AI agents (e.g., Claude Code or similar) to support analytical workflows
BONUS EXPERIENCE:
- B2B SaaS, subscription, or platform business with direct sales motion
- Finance/FP&A, consulting, or investment analysis background before moving into analytics
- Experience designing or advising on sales compensation plans
- Experience building predictive models (churn, LTV) actually adopted into team workflows
- Familiarity with HubSpot or comparable CRM and contact-centre data (e.g., Twilio)
- Experience working in small teams and startup environments
