Finance Data Scientist in London

Euromonitor International leads the world in data analytics and research into markets, industries, economies and consumers. We provide truly global insight and data on thousands of products and services; we are the first destination for organisations seeking growth. With our guidance, our clients can make bold, strategic decisions with confidence.

The Finance Data Analyst / Scientist plays a central role in transforming how Finance, Operations, and Commercial teams leverage data to drive decision making. This hybrid position blends deep financial expertise with advanced analytics, data modelling, and visualisation/presentation capabilities. The role supports both structured reporting and highly analytical, ad hoc problem solving, ensuring that the organisation has accurate, trusted, and forward-looking insight.

A key focus is to modernise financial reporting, streamline forecasting, and build scalable analytical products that enhance business understanding. This role is critical in bridging Finance with Technology and Data teams, ensuring that financial logic, controls, and definitions are correctly embedded in data products and reporting systems. The role requires a confident presenter able to communicate, collaborate and gain buy-in across a wide variety of stakeholders.

• Deliver advanced financial analysis, modelling, and scenario planning.
• Support FP&A cycles, including budgeting, forecasting, and performance reviews.
• Translate complex datasets into actionable recommendations for senior leadership.
• Provide insight across revenue, cost, margin, headcount, and operational KPIs.
• Support people analysis to ensure we understand our cost base and are able to report/forecast/scenario plan efficiently to a high standard.

• Support the building of predictive, statistical, and machine learning models to support forecasting and performance analysis.
• Use techniques such as regression modelling, clustering, forecasting algorithms, anomaly detection, and classification.
• Work with large datasets across Finance, Operations, Commercial, and People/Reward functions.
• Apply analytical thinking to solve ad hoc and strategic business challenges.

• Develop robust Power BI dashboards using Power Query, DAX, and strong data modelling practices.
• Enhance and maintain existing dashboards including financial performance, workforce planning, sales compensation, and operations insight.
• Build automated data refresh processes and reporting pipelines.
• Translate business requirements into intuitive, high impact dashboards.

• Validate and map data from core systems including Dynamics 365 Finance, Salesforce, and SaaS billing platforms.
• Own and maintain finance KPI definitions, ensuring alignment across reporting tools.
• Embed reconciliation logic, audit requirements, and financial controls within data pipelines.
• Work closely with Data Engineering to ensure models are scalable, well documented, and governed.

• Lead and manage analytical projects spanning FP&A, Commercial, Ops, HR/Reward, and Tech.
• Support the business with modelling for compensation, sales commissions, workforce analytics, bonus modelling, and scenario analysis.
• Collaborate with stakeholders to refine project objectives, timelines, and deliverables.
• Support monthly, quarterly, and annual modelling cycles (e.g., bonus files, salary review models, workforce dashboards).

• Champion the evolution of finance data architecture and reporting standards.
• Identify opportunities for automation and operational efficiency.
• Promote data literacy within Finance and the wider business.
• Collaborate with the Data Product Manager to define data requirements and analytics priorities.

• ACCA / CIMA / ACA qualified or part qualified strongly preferred.
• Strong understanding of forecasting, budgeting, cost/margin analysis, financial controls, and month-end processes.
• Experience in FP&A, commercial finance, operational analytics, or similar finance roles.
• Experience in producing dashboards & recommendation-led analysis covering people data/analytics including variable compensation (bonuses/commissions/annual pay reviews).

• Advanced Power BI skills including DAX, Power Query, M language, and data modelling.
• Degree in Finance, Economics, Data Science, Mathematics, Engineering, Statistics, or similar.
• Certifications in analytics, Power BI, SQL, Python, AI/ML, or cloud data platforms are an advantage.
• Strong SQL skills for querying and transforming data.
• Experience with Python or R for statistical analysis, modelling, and automation.
• Familiarity with data lakehouse environments and modern cloud-based data platforms.
• Ability to convert business rules and finance logic into structured data models.
• Comfort working with APIs, large datasets, and multiple system integrations.
• Strong PPT/reporting skills and extensive experience in presenting dynamically to senior company leadership level.
• Proactive in using, testing and benefiting from AI both in terms of efficiency, but also proactive analysis/improvements to support business growth.

• Predictive modelling and machine learning experience.
• Familiarity with libraries such as scikit-learn, pandas, NumPy, or equivalent.
• Understanding of model evaluation, feature engineering, and algorithm selection.

• Excellent communication skills – able to explain & present complex data clearly to non-technical audiences and deliver the ‘so what’ to enable effective decision making.
• Strong project management, able to juggle multiple priorities and deadlines.
• High attention to detail and a logical, problem-solving mindset.
• Ability to work independently with minimal guidance and collaborate effectively with cross functional partners.

• Delivery of high quality, timely insights that drive decision making.
• Power BI dashboards become trusted sources of truth across the organisation.
• Predictive and analytical models materially improve forecasting and operational performance.
• Finance logic and data definitions are consistently applied across systems.
• Ability to automate and reduce manual reporting to improve accuracy.
• Strong, productive relationships built across Finance, Research, Ops, Sales, Data Engineering, and HR/Reward.
• Clear, well documented data models and processes that future-proof reporting.
• Effective handling of ad hoc analytical projects with clarity, structure, and measurable impact.

This is a high impact, forward looking role that blends financial acumen with data engineering alignment, analytics capability, and business partnering. It is ideal for someone who enjoys solving ambiguous analytical problems, building scalable dashboards and models, and modernising how Finance uses data.