Finance Data Scientist

About Euromonitor 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. About the role The Finance Data 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. This hybrid position blends deep financial expertise with advanced analytics, data modelling, and visualisation skills, ensuring that the organisation has accurate, trusted insight. The role will collaborate closely with FP&A, Finance, Data Engineering, Data Product Manager, HR/Reward teams, Sales Ops, Senior Business Leaders and other business partners. 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. What you’ll do • Lead and deliver financial analysis, modelling and scenario planning • Support FP&A cycles, including budgeting, forecasting, and performance reviews • Build and enhance Power BI dashboards (Power Query, DAX, strong data modelling) that become “sources of truth” across revenue, cost, margin, headcount and operational KPIs. • Develop predictive and statistical models (e.g., regression, classification, anomaly detection, clustering) to improve forecasting and operational performance. • Translate business rules and finance logic into robust, governed data models; embed reconciliation logic and financial controls within data pipelines. • Partner closely with FP&A, Finance, Data Engineering, the Data Product Manager, HR/Reward, Sales Ops and senior business leaders on high‑impact analytical projects and ad hoc problem solving. • Automate refreshes and reporting pipelines; streamline manual reporting into reliable, repeatable processes. What you’ll bring Finance Expertise • ACCA / CIMA / ACA (or equivalent) 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 Technical & Analytical Skills • 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. Data Science Capability • 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. </li&g