Pricing Lead
The Pricing Lead owns how Numan prices. You'll define the pricing strategy for each category, then build and run the roadmap of tests that gets us there, one experiment at a time. You'll sit in the Commercial team, reporting to the VP of Commercial, and your work will shape what patients pay and how profitable Numan is.
This is an AI native role. You'll use AI every day to analyse our own pricing data and the market around us: competitor moves, switching patterns and how patients respond to price. You'll turn what you find into sharp hypotheses, and those hypotheses into tests. The faster that loop runs, the faster we learn.
Ideally you'll come from growth. You'd rather ship a test this week than a perfect model next quarter. You hunt for quick wins without losing sight of the long game, and you know when the data says stop.
You will:
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Define the pricing strategy for each category: price architecture, discount and promo rules, commitment packages and the guardrails category leads work within. Keep it current as the market moves.
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Turn the strategy into a prioritised roadmap of pricing tests, each with a clear hypothesis, expected impact and success measure. Let each result decide what you test next.
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Use AI to analyse internal pricing performance and external signals at speed, including competitor pricing, propositions, reviews and switching behaviour. Turn the patterns into testable hypotheses.
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Design and launch tests with Growth, Marketing and Finance. Set guardrails before launch, read results with statistical rigour, and scale or kill fast.
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Own the pricing view of revenue, margin and unit economics by category, product and cohort. Support quarterly planning and forecasting with Finance, and flag risks and opportunities before they reach the P&L.
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Build the financial case for new propositions, launches and pricing changes, including payback and ROI.
You will have:
- A degree in Data Science, Mathematics, Economics, Finance or another science or quantitative subject
- 4+ years in pricing, growth or commercial analytics, with tests you can point to that moved revenue or margin
- AI native: you use AI daily for analysis, research and modelling, and can show where it changed what you found or how fast you found it
- Strong experiment design and the statistics behind it
- Strong financial modelling, and fluent in unit economics: CAC, LTV, contribution margin, cohort retention
- A clear, persuasive communicator who turns complex analysis into a decision
