This role is right for you if you thrive in a fast-paced environment, think like an operator rather than just an analyst, enjoy a challenge, and want to make a significant impact on how a fast-growing commercial engine actually runs.

How we work

We're rebuilding Analytics around three principles: understand what's really going on, not just report the number that was asked for; partner with the business, rather than simply serve it; and raise what matters before you're asked, rather than waiting for a request. This sits alongside Fresha's wider values — Accountability, Curiosity, Unity, Bravery, and Excellence.

Key accountabilities

Behavioural

• Collaborate broadly across Commercial, Finance, and Analytics to align on priorities and create solutions that work in practice, not just on paper
• Own day-to-day task and priority management for the Commercial pod, supporting the Head of Analytics on broader roadmap planning
• Raise what matters before you're asked — flag opportunities and risks proactively rather than waiting to be asked
• Drive a fair, supportive working environment for the analysts in your pod, bringing a positive, can-do attitude to hard or ambiguous problems
• Prioritise pragmatically, balancing commercial impact against effort and dependencies, and stay close enough to the business to know what's actually urgent

Technical

• Design decision-support systems that surface opportunities and risks for Account Management and CRM teams, prioritise action, and track outcomes against revenue and retention
• Own analytics for Fresha's Commercial function — Direct Sales performance, Account Management and Retention, and Customer Experience/Partner Support operations
• Build and own unit economics models for the commercial engine — direct sales, acquisition cost, lifetime value, margin, and how compensation structures affect them
• Design and evolve compensation and incentive structures for Direct Sales and Account Management, closely aligned with pricing strategy, moving beyond revenue/GP targets alone toward incentives that are more immediately motivating and easier to track
• Own forecasting for key commercial metrics — retention, churn, revenue growth, customer success
• Build predictive models (e.g. churn risk scoring) where they materially improve how the team prioritises action
• Design and run experiments to test compensation, pricing, or retention interventions, with statistically rigorous read-outs
• Drive automation of customer support insight generation using modern data and AI tooling, reducing manual reporting overhead
• Write production-grade SQL and Python, and use AI-assisted development tools (Claude Code or similar) as a normal part of how you work

Skills, experience & qualifications required

• 6-10 years in a senior analytical role with a strong commercial analytics, finance, FP&A, or retention analytics background, ideally including 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 working with a modern data stack (we run Snowflake and dbt); our internal BI tool is Python-based (Plotly), though experience with any modern BI tool is fine
• 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 the data doesn't support the proposed direction
• Fluent use of AI agents (e.g. Claude Code or similar) to support analytical workflows

Bonus points

• Experience in a B2B SaaS, subscription, or platform business with a direct sales motion
• Background in finance / FP&A, consulting, investment analysis before moving into analytics
• Experience designing or advising on sales compensation plans
• Experience building predictive models (churn, LTV) that were actually adopted into a team's workflow
• Familiarity with HubSpot or a comparable CRM, and with contact-centre data (e.g. Twilio)
• Experience working in small teams and startup environments

Inclusive workforce

At Fresha, creating a culture where individuals of all backgrounds feel comfortable matters.

We want all Fresha people to feel included and truly empowered to contribute fully to our vision and goals. Everyone who applies will receive fair consideration for employment.

We do not discriminate based upon race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.

If you have any accessibility requirements that would make you more comfortable during the interview process and/or once you join, please let us know so that we can support you.