Marketing Solutions Senior Analyst

The Senior Analyst role exists to take ownership of analytical workstreams within Marketing Solutions client engagements and ensure that work is delivered accurately, efficiently and to a consistently high standard. The individual will combine hands-on analysis with stakeholder communication, quality assurance and support for the development of junior colleagues.

• Translate business and client requirements into structured analytical questions, workplans, data requirements and delivery priorities.
• Take ownership of data collection, preparation, validation and analysis across assigned client workstreams.
• Investigate complex datasets to identify trends, anomalies, relationships and potential drivers of business performance.
• Review data inputs and analytical outputs, resolving discrepancies and ensuring that work is accurate, documented and ready for modelling or client delivery.
• Support Marketing Mix Modelling and other marketing effectiveness engagements by preparing model-ready data, reviewing inputs and outputs, and helping translate results into clear business implications.
• Develop forecasts, recommendations and strategic or tactical actions based on analytical findings, business context and market knowledge.
• Create clear, decision-focused outputs in Microsoft Excel and Microsoft PowerPoint for internal and client stakeholders.
• Explain complex analytical findings in straightforward language and contribute confidently to internal and client discussions.
• Manage assigned workstreams against agreed timelines, proactively identifying risks, dependencies and resource requirements.
• Review the work of junior analysts, provide practical coaching and help maintain consistent quality standards across the team.
• Collaborate with consulting, data, modelling, engineering and delivery colleagues across the India GCC, UK and wider global organisation.

Required Knowledge and Experience

• Approximately two to three years of relevant experience in analytics, data analysis, data-led consulting, research or a related field, including experience independently owning analytical tasks or workstreams.
• Strong quantitative and analytical knowledge, with the ability to structure complex problems, challenge assumptions and translate analysis into practical recommendations.
• A degree in statistics, mathematics, economics, engineering, data analytics or another quantitative discipline is preferred because the role requires independent interpretation of complex data and analytical outputs. Equivalent practical analytical experience will also be considered.
• Practical knowledge of data preparation, validation and quality-assurance frameworks, including experience identifying and resolving data-quality issues before delivery.
• Experience communicating analytical findings to colleagues or stakeholders. Previous client-facing experience is desirable because the role will contribute to discussions and help explain analytical outcomes.

Required Technical Skills

• Advanced Microsoft Excel, including complex formulas, pivot tables, lookups, data manipulation, reconciliation and quality-control processes.
• Strong Microsoft PowerPoint skills, with the ability to create clear, structured and decision-focused presentations.
• Practical experience working with large, complex and multi-source datasets.
• Working knowledge of SQL, Structured Query Language, or another data-querying or analytical tool.
• Ability to review analytical work, identify potential errors and communicate findings clearly in written and verbal English.

Preferred Skills

We’re also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we’re happy to support your career development and growth in:

• Experience with Python, R or another analytical programming language.
• Experience with visualisation tools such as Microsoft Power BI or Tableau.
• Exposure to Marketing Mix Modelling, marketing effectiveness, attribution, customer analytics or commercial performance analysis.
• Experience applying statistical methods such as regression, forecasting, hypothesis testing or time-series analysis.
• Experience reviewing the work of junior colleagues, coordinating analytical tasks or providing coaching and technical guidance.