Commercial Data Analyst

We are the Intelligent Internet Platform. We connect People, Places and Things anywhere, managing Internet Performance better than anyone else, while providing One Global Experience, giving Visibility, Control and Security through expereoOne.

Expereo believes in the power of Internet connectivity. As the world's largest provider of managed internet, SD-WAN/SASE, and Cloud connectivity solutions, we power enterprises and government sites worldwide, helping to enhance every business' productivity with flexible and optimal Internet performance.

As a trusted partner of Fortune 500 enterprises and carriers, our continued aim and success in helping both our customers and partners depends solely on the talented individuals that make Expereo a dynamic, effective, multicultural, and equitable environment. 

The Role

We are looking for a commercially minded Data Analyst to join our team, working directly with costing and pricing data at the heart of our quote engine platform. This role sits at the intersection of data quality, commercial insight, and pricing performance, giving you direct visibility into the decisions that shape how Expereo wins and grows business globally.

You will be the analytical backbone of the commercial team: owning reporting, managing the data that feeds our predictive models, and building the self-serve dashboards and visualizations that let sales, finance, and commercial stakeholders act on insight without waiting for an analyst. Experience with pricing, whether in B2B SaaS, telecoms, logistics, or a similarly complex commercial environment, is strongly preferred and will be central to how you add value from day one.

• Key Responsibilities
• 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.