Data Analyst - Commercial Performance

About the role

This Data Analyst role focuses on tracking business and commercial performance through dashboards, reports and data modelling. It works closely with the Commercial, Product, Technology and Operations teams to turn data into actionable insights.

Key responsibilities

• Build and maintain dashboards, scorecards and reports on key business and commercial metrics.
• Analyse accounts, partners and business performance data to find trends, opportunities and improvements.
• Support budgeting, forecasting and business planning with data modelling and scenario analysis.
• Measure the impact of sales initiatives, partnerships and growth strategies.
• Conduct market sizing, competitive analysis and industry research to support pricing and growth.
• Develop partner performance scorecards and support quarterly business reviews.
• Produce executive-ready reports and presentations with clear recommendations.
• Work with Commercial, Product, Technology and Operations teams to improve reporting and data quality.
• Use internal and external data to quantify addressable market opportunities and support new business initiatives.
• Perform ad-hoc analyses and special projects.

Required profile

• Bachelor's degree in Business Analytics, Statistics, Mathematics, Economics, Computer Science or a related field.
• 1-3 years of experience in data analytics, business intelligence, commercial analytics or a similar role.
• Strong analytical mindset and ability to interpret data and spot business trends.
• Ability to translate business requirements into analyses and communicate findings clearly to stakeholders.
• Detail-oriented, with strong problem-solving and organisational skills; able to handle multiple projects in a fast pace.
• Preferred: B2B, mobility, transportation, logistics or technology industry experience, and exposure to sales performance, customer segmentation, revenue analysis or commercial reporting.

Required skills

• SQL and Microsoft Excel for data extraction, analysis and reporting.
• Data visualisation and dashboarding tools such as Power BI.
• Preferred: Python or other analytical tools.