Offering Tools Finance Lead at Everpure in London
- Company: Everpure
- Location: London, United Kingdom
- Job type: full time
- Workplace: hybrid
- Posted: 2026-10-20
Job description
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. Offering Tools Finance Lead Purpose Everpure is looking for a Business Case Finance Lead to build the financial models behind customer business cases. You will build CFO-grade, repeatable and standardised value logic for products across Everpure's portfolio, and own the assumptions, benchmarks and inputs that keep those models accurate. The models feed directly into our wider automated sales operating model, so sellers everywhere present customers with the same credible, defensible numbers. These models will underpin the proposals used across the entire sales organisation, and form the core of the business cases that go in front of customers. They will cover a wide range of deal sizes, products and industries, so they need to be consistent, robust and adaptable. The role has three parts: Identify the value. Understand how each product creates measurable value for customers, across cost efficiency, growth or protection, sustainability and risk reduction. Build the model. Convert that value into a repeatable, standardised financial model, including cash flow, P&L and return metrics, that works across accounts and deal sizes. Tell the financial story. Translate the model and its outputs into a clear, compelling financial narrative that increases the impact of every proposal with customers, including their CFOs and finance teams. What Success Looks Like Credible, robust and accurate financial models underpin the portfolio of Everpure products. Models are repeatable and standardised, and can be fed into customer proposals through our wider automated operating model. Models and financials are translated into a compelling financial narrative that resonates with customers, including CFOs and finance teams. Governance is in place around model inputs, with assumptions validated, updated and maintained. Existing models are continually refined as new data is collected and new products are released. What You'll Be Doing Value and Financial Models Identify how each product creates measurable value for customers across the key value levers: cost efficiency, revenue growth or protection, sustainability and risk reduction. Build CFO-grade financial models, including cash flow and P&L, for each product across the portfolio. Standardise models around common inputs and outputs, so they can be repeated efficiently and consistently across accounts and products. Apply a consistent methodology and accounting treatment, with ROI, TCO, NPV, IRR and payback calculated the same way every time. Continuously improve model accuracy, and develop new, financially robust ways to quantify value. Financial Narrative Translate model outputs into a clear, compelling financial narrative that shows customers what the investment means for their business. Turn complex financial results into tangible measures that customers and sellers can relate to. Help sellers position the business case confidently, in executive language. Assumptions, Inputs and Governance Own, govern and maintain the global assumptions, benchmarks and financial inputs feeding the models. Identify and add the new pricing, product advances and market trends the models need, within an agreed SLA. Define the source, owner and refresh cadence for every input, and maintain a clear version history. Reconcile model outputs against real deals to check accuracy over time. Documentation and Support Document each model's logic, inputs and outputs clearly enough for i
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