Commercial Strategy & Analytics Associate
Listed on 2026-07-03
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IT/Tech
Data Analyst, Business Systems/ Tech Analyst
Commercial Strategy & Analytics Associate
Department: Commercial
Employment Type: Permanent
Location: London
Reporting To: Eoin O'Kane
DescriptionWe’re looking for a Commercial Strategy & Analytics Associate to help You Lend find, test and scale high-impact growth opportunities across our embedded finance platform.
You’ll work closely with our Product, Risk, Pricing, Data and partner-facing teams. Your role will be to turn ambiguous commercial questions into robust analysis, experiments, tools and recommendations that help us grow funded volume, improve conversion, reduce friction and make better decisions.
This is a hands‑on analytical role. You’ll need strong SQL, Excel/Sheets and Python or similar coding ability. You should be comfortable digging into messy data, understanding product flows, reading technical documentation, getting to grips with logic or configuration, and working with technical teams to understand what is really happening.
You are not a software engineer, but you do need to be curious and technical enough to follow the thread: from a dashboard, into the data, into the product or decisioning logic, and back to a clear commercial recommendation.
You’ll also know when it’s the right time to take a step back from the analysis and find the right person who can unblock an issue, whether that be someone inside You Lend or within a partner.
The right person will be analytical, practical, commercially curious and excited by experimentation. They’ll also be pragmatic: comfortable using AI tools, Codex, Replit, notebooks or lightweight scripts to build proof‑of‑concepts, validate ideas quickly and create evidence for more durable product or data solutions.
Key Responsibilities- Own commercial experiments end to end: define the hypothesis, design the test, agree success metrics, monitor results and recommend the next action.
- Analyse growth opportunities across offers, pricing, eligibility, renewals, customer journeys and partner performance.
- Use SQL, Excel/Sheets and Python or similar tools to get underneath dashboards and understand what is actually driving performance.
- Improve the data foundations behind commercial experimentation, including funnel tracking, event definitions, metric quality and test measurement.
- Work with Product, Risk, Pricing and Data to turn commercial ideas into tests, product changes, decisioning logic or operational improvements.
- Build models to assess trade‑offs between conversion, funded amount, risk, pricing, margin and customer experience.
- Improve how we track key funnels, so we can understand what customers saw, what they did next, and whether a change worked.
- Use partner and first‑party data to identify opportunities to improve targeting, offers, decisioning or conversion.
- Build lightweight proof‑of‑concepts, dashboards, scripts and AI‑assisted tools where they help validate an idea quickly.
- Translate technical analysis into clear recommendations that Commercial, Product, Risk and senior stakeholders can act on.
You might work on questions such as:
- How should we set early renewal eligibility to maximise incremental funding without creating unacceptable risk?
- What offer should we show a merchant before they apply, and how does that affect application rate, conversion and final funded amount?
- How should we design an A/B test to understand whether a pricing, eligibility or journey change actually improves outcomes?
- Which customer segments should receive different offer structures based on conversion, returns and profitability?
- Where are instant or automated offers underperforming manual review, and what logic or journey changes would close the gap?
- How can we use partner data more effectively to improve targeting, decisioning, pricing or customer experience?
- What lightweight tool, dashboard or AI prototype could help Commercial teams answer a recurring question faster?
After 6‑9 months, you’ll be independently owning commercial analytics and experimentation work streams: identifying the right opportunity, getting into the data, designing a sensible test or analysis, aligning the right teams and turning the result into action.
You’ll have helped You Lend make better decisions on…
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