Analytics Manager in City of London

Base pay range

This range is provided by Klarna. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

What you’ll do

• Deal evaluation & investment cases: Build and own business cases for partner pricing, subsidies, and co-marketing investments; run scenarios, sensitivities, and break-even analyses to recommend the optimal structure.
• Sales & marketing forecasting: Develop robust forecasts for volume, revenue, and contribution margin across channels and partners; quantify upside/downside, and explain drivers in plain English.
• P&L ownership at deal level: Connect commercial terms to unit economics (take rate, funding, fees, losses, opex) and show the impact on merchant/segment P&L and Klarna profitability.
• Measurement & ROI: Define KPIs and post-investment reviews; build simple frameworks to measure payback, incrementality, and LTV/CAC for campaigns and partnerships.
• Pricing & terms support: Partner with Sales on proposals; translate data into negotiation guardrails, and articulate the “so what” for senior stakeholders.
• Insight to action: Turn ambiguous questions into structured analysis, create clear “exec-ready” narratives, and drive decisions through written docs and visual dashboards.
• Automation & tooling: Use SQL/Python to source and transform data; build reliable datasets and dashboards (Looker/Tableau/Power BI) that scale beyond one-off analyses.
• Cross-functional collaboration: Work closely with Commercial, Marketing, Finance, Data/Engineering, and Risk to align assumptions, surface trade-offs, and land decisions.
• Governance & cadence: Contribute to the rhythm of reviews (e.g., investment forums, pricing/deal desk), ensuring proposals are decision-ready and outcomes are tracked.

What you’ll bring

• Core analytical toolkit: Advanced Excel/Sheets and strong SQL; working proficiency in Python (pandas, modelling/forecast workflows).
• Financial fluency: Solid grounding in P&L analysis, valuation, and investment appraisal; comfort with unit economics, cohort analysis, and scenario modelling.
• Relevant experience: Background in corporate finance, FP&A, strategy, or a highly analytical commercial role—ideally within tech, payments, or e-commerce.
• Forecasting & evaluation: Demonstrable experience building driver-based forecasts and evaluating marketing or commercial investments with clear ROI logic.
• Business judgement: Ability to link financial outcomes to commercial, marketing, and sales performance; pragmatic about signal vs noise.
• Communication: Clarity in written docs and slides; confident presenting to senior audiences and simplifying complex topics into actionable recommendations.
• Ways of working: Comfortable in fast-paced, data-rich environments with shifting priorities; high ownership, bias to action, and attention to detail.

Nice to have

• Exposure to M&A, partnerships, or complex commercial contracts.
• Experience with data modelling/engineering concepts (e.g., dbt, version-controlled analytics code) and CI-friendly analytics workflows.
• Familiarity with experimentation and incrementality (A/B testing, MMM concepts) and marketing performance measurement.
• Knowledge of payments economics (funding costs, risk/loss dynamics) or BNPL/fintech unit economics.

How success will be measured

• Accuracy and clarity of forecasts (and the narrative explaining variance).
• Quality and impact of investment proposals (speed to decision, realised ROI).Reusability of assets (datasets, dashboards, templates) and reduction of ad-hoc effort.
• Stakeholder feedback from Commercial, Marketing, and Finance leadership.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Analyst

Industries

Software Development