Data Quality & Reporting Controls

• Own the accuracy and consistency of reports and models produced or maintained; reconcile key figures to agreed sources and investigate material discrepancies.
• Document definitions, assumptions, validation checks and material changes so outputs can be understood, reproduced and used consistently.
• Escalate source-data, integration or platform failures to the responsible internal owner; explain the impact and validate corrected reporting before wider use.
• Maintain usable handover notes for critical reports and planning models, including access requirements and recurring steps, so delivery does not depend on one individual.

Business Partnering & Client Support

• Work with Sales, Marketing, Category, Pricing, Finance, Operations and leadership to understand commercial priorities and ensure planning, reporting and analysis support effective decision making.
• Produce clear commercial and client review packs, explaining the main findings, risks, recommended actions and decisions required.
• Help non-technical stakeholders use dashboards, understand KPI definitions and apply insights to planning and trading decisions.

Technical Collaboration

• Personally configure, maintain and troubleshoot agreed reporting and tracking settings across Google Ads, Google Merchant Centre and Google Analytics, within authorised access and change controls.
• Maintain routine account links, measurement settings and feed/reporting configuration as required; test and document changes and verify the data received.
• Define requirements and validate outputs with internal technical owners where changes need tagging, code, backend integrations or pipelines. Technical ownership, security and access governance remain with Tech.

Project & Operational Support

• Support cross-functional projects with analysis for strategy, investment and operational planning decisions.
• Curious and proactive in exploring how AI can improve ways of working, with a willingness to adopt new tools that reduce repetitive manual tasks and create more time for higher value work.
• Maintain a prioritised reporting and analysis plan that protects agreed reporting, forecast and budget deadlines; raise capacity conflicts early with options and recommendations.
• Challenge inaccurate, manual or low-value reporting practices; explain the benefit of change, implement agreed improvements and verify results without repeated prompting.
• Undertake other agreed duties consistent with the role's commercial analytics and planning remit.

Reporting Structure

• Reports to: Head of Sales
• Direct reports: 0
• Key internal interfaces: Head of Sales, Head of Marketing, Growth Marketing Manager, Trading Marketing Manager, Sales / Account Management, Category Management, Pricing, Finance, Tech / BI, Operations
• Technical interfaces: Internal owners of SQL databases, Power BI platform administration, data pipelines, technical integrations and platform performance.

Success Measures (KPIs)

• Reporting accuracy and reliability: Agreed outputs delivered on time; material errors, rework, correction time and prevention of repeat issues.
• Forecast accuracy: Accuracy using an agreed method, quality of assumptions and timely variance explanations, considered alongside trading conditions and stakeholder inputs.
• Sales plan integrity: Accuracy, completeness and timeliness of the annual Ford sales plan and in-year forecasts; quality of assumptions and governance; effective integration of regional sales and category initiatives; and early identification and resolution of gaps, risks and inconsistencies.
• Commercial intelligence impact: Evidence that analysis identified high impact risks, opportunities and areas for improvement early enough to influence commercial decisions and action, rather than report or analysis volume.
• Dashboard adoption and usability: Stakeholder usage, feedback and reduction in recurring manual reporting requests.
• Automation and efficiency: Verified reduction in recurring manual work while preserving reporting checks, documentation and continuity.
• Google reporting and tracking reliability: Accurate, complete outputs; timely diagnosis, controlled configuration changes, validated fixes and follow-up of technical dependencies.

Skills & Experience Essential

• Proven experience as a Data Analyst, BI Analyst, Commercial Analyst or similar role in a fast-paced commercial or operational environment. Demonstrable experience owning or playing a lead role in a commercial sales planning and forecasting process, bringing together multiple stakeholder inputs, challenging assumptions and monitoring delivery against plan.
• Strong SQL skills with the ability to manipulate, join and query large datasets efficiently.
• Hands-on Power BI proficiency from day one, including report and dashboard development, reporting models, calculations and validation; normal induction covers the company's data and processes.
• Experience developing or maintaining commercial forecasts and planning models, testing assumptions and explaining variances.
• Proficient in Microsoft Excel and confident working with planning models, reporting templates and data validation.
• Commercial understanding of sales, marketing, product and customer KPIs, including the distinction between GMV, revenue, margin and attributed performance.
• Strong communication skills, with the ability to translate complex data into clear narratives for stakeholders and clients.
• High attention to detail, strong organisation and the ability to manage competing priorities.
• Practical experience configuring and troubleshooting reporting, tracking and account connections across Google Ads, Google Merchant Centre and Google Analytics, with testing and documented change control.
• Evidence of independently identifying and delivering commercial, planning or reporting improvements, using data to identify the opportunity, recommend action and measure the result.

Skills & Experience Desirable

• Experience with cloud-based data platforms such as Azure, AWS, Google Cloud, BigQuery or Snowflake.
• Working knowledge of Python, R or similar tools for deeper analysis or automation.
• Awareness of ETL processes, data pipelines or data warehousing concepts.
• Exposure to ecommerce, marketing, sales or supply chain analytics.
• Educated to degree level in a relevant field such as Data Science, Analytics, Business, Mathematics or Computer Science, or equivalent practical experience.

Personal Attributes / Behaviours

• Commercially curious and action-oriented; looks beyond what the data says to understand why it is happening and what could be done better.
• Analytical and precise; checks assumptions and investigates discrepancies.
• Challenges established approaches constructively and clearly explains the benefit of change.
• Communicates clearly and credibly with commercial and technical stakeholders.
• Takes initiative, owns deadlines and follows through without repeated chasing; raises material risks early.
• Collaborates effectively with Sales, Category, Marketing, Pricing, Finance and Tech while retaining clear accountability for the integrity of the sales planning process, commercial intelligence and reporting outputs.