Produce regular reporting on pricing performance, margin outcomes, and win/loss trends across customer segments and geographies.
Maintain and QA the historical cost dataset that feeds predictive costing models, flagging anomalies and gaps to ensure clean input into the model.
Translate OKR targets into trackable dashboards that give commercial and finance teams clear visibility on progress, ensuring targets are grounded in data and measurable.
Conduct ad hoc analysis to support pricing decisions benchmarking margins by product or region, identifying accounts at risk of churn, or stress-testing proposed price changes.
Build self-serve reporting tools so that sales, commercial, and finance stakeholders can explore pricing and cost data without analyst involvement.
Work with other data scientists to validate model outputs against business intuition and historical benchmarks before they go live.
Support our next-generation product modelling by cataloguing existing product structures, cost components, and pricing rules as a foundation for the new quote engine.

Demonstrable experience working with pricing data in a commercial context — margin analysis, cost benchmarking, win/loss reporting, or equivalent.
Strong proficiency in SQL and Python/R for data extraction, transformation, and analysis
Experience building dashboards and reporting tools (Power BI, Tableau, MicroStrategy, or similar)
Rigorous approach to data quality: able to identify anomalies, trace root causes, and implement fixes that stick.
Ability to communicate analytical findings clearly to non-technical commercial and finance stakeholders.
Experience documenting data lineage and metric definitions in a way that scales across teams.
Background in B2B SaaS, telecoms, or logistics, where pricing complexity and margin discipline are real commercial stakes.
Familiarity with predictive costing or pricing models and experience validating their outputs against actuals.
Exposure to AWS data services (S3, Athena, Redshift) or equivalent cloud infrastructure.

A small, high-trust team working on genuinely hard commercial problems with direct business impact.
Direct access to production data and decision-makers, no layers of process between your work and its outcomes.
A role with clear trajectory: the commercial and technical context you build here is a natural path toward senior analytical or technical execution responsibilities.
Competitive compensation and local benefits

Commercial Data Analyst

Key skills