Strategy Analyst

Strategy Analyst (Commercial)

As a Strategy Analyst in the commercial team, you will work across commercial forecasting and partner-level pricing to support growth optimisation. You will build and maintain the models, dashboards, and analytical infrastructure that underpin how we plan, track, and improve commercial performance. Your analysis and recommendations will directly inform partner strategy, pricing decisions, and performance management across Commercial, Risk, Capital Markets, Operations, Partnerships, and Product. This role is ideal for someone who wants to build systems—not just run analyses—and is excited by seeing their work shape commercial outcomes.

Annual salary: £42,000 - £54,000 OTE

Responsibilities

• Support the production and continuous improvement of commercial forecasts, including inputs, outputs, scenarios, tracking, and variance analysis.
• Build and maintain dashboards, self-serve data infrastructure, and tools (e.g., in Metabase) used across Commercial, Risk, Ops, and Capital Markets.
• Produce driver breakdowns and structured performance summaries (leads, conversion, funded amount, mix).
• Run monthly recalibration and variance decomposition to explain under- and overperformance.
• Identify weaknesses in forecasting and implement improvements to modelling, input structures, and processes.
• Analyse partner performance and pricing dynamics to identify growth opportunities.
• Size the impact of pricing to optimise for commercial changes.
• Support the development of structured commercial proposals and pricing recommendations.
• Track commercial levers (expected vs actual impact) and run retrospectives on implemented changes.
• Monitor partner performance post-change and flag opportunities or issues.
• Improve data structures to reduce manual work, duplication, and ad-hoc requests.
• Make recommendations that guide partner strategy and commercial decisions across teams.

Qualifications & Requirements

• Interest in fintech, lending, and commercial strategy.
• 1-3 years of experience in an analytical, data, or commercially oriented role, or a strong graduate with relevant quantitative experience (e.g., coding in Python, R, Stata, or SQL).
• Strong SQL capability (required) and modelling skills in Excel; Python preferred, though experience with other analytical languages is valued.
• Ability to build from scratch: models, dashboards, and analyses—not just work with existing outputs.
• Clear, structured written communication: translate analysis into insight and recommendations.
• High ownership mindset: follow through and take responsibility for outputs.
• Comfortable working with ambiguity and bringing structure where processes are not yet fully defined.
• Proactive approach: look for improvements, not just instructions.
• Curiosity about commercial outcomes, not just the numbers behind them.
• Team-first mindset: collaborative and willing to work across teams to get things right.