We are seeking a highly analytical and detail-oriented Finance Analyst to support the commercial finance team in understanding and forecasting player behaviour, with a particular focus on player churn and retention. The successful candidate will design, build, and maintain a robust Excel-based cohort model that quantifies churn dynamics, supports financial forecasting, and helps guide strategic decisions around player lifetime value, marketing ROI, and retention initiatives. This is a hybrid role, based on site 2 days a week at our Cambridge studio. Responsibilites Model Development & Maintenance Design and build a dynamic Excel model to track and forecast player churn by cohort, incorporating key behavioural and financial metrics (e.g. acquisition date, spend, activity, retention curves). Maintain and update the model regularly with new data from finance and data analytics teams. Ensure the model is transparent, auditable, and scalable for future business needs. Data Analysis & Insights Analyse player lifecycle data to identify churn drivers, retention trends, and revenue impacts. Segment players into cohorts (e.g. by acquisition channel, geography, game title, or spend level). Work closely with marketing and product teams to quantify the impact of retention campaigns or game changes. Financial Forecasting & Reporting Integrate churn assumptions into revenue and cash flow forecasts. Support budgeting and scenario modelling by providing insight into expected churn rates and lifetime values. Prepare and present findings to finance leadership and key stakeholders across the business. Collaboration & Cross-Functional Work Partner with Data, Marketing, and Product teams to align definitions and data inputs. Collaborate with BI and data engineers to automate model inputs over time (e.g. via SQL or Power Query). Translate complex analytical outputs into clear, actionable insights for non-technical stakeholders. Requirements Essential: Strong Excel skills, including advanced formulas, data modelling, Power Query, and data visualisation (PivotTables, Charts). Experience building financial or analytical models from scratch. Excellent quantitative and analytical skills with a keen attention to detail. Strong understanding of cohort analysis, churn modelling, or customer lifetime value (LTV) metrics. Ability to communicate insights clearly to senior non-technical audiences. Relevant degree in Finance, Economics, Mathematics, or related field. Desirable: Experience in gaming, entertainment, or subscription-based businesses. Familiarity with SQL or data extraction from BI tools (e.g. Looker, Tableau, Power BI). Exposure to Python, R, or other statistical tools for churn or retention modelling. Understanding of digital marketing metrics and player acquisition funnels. Personal Attributes Curious and data-driven with a proactive approach to problem solving. Comfortable managing large, complex datasets. Strong business acumen – able to link data insights to financial performance. Excellent communication and stakeholder management skills. Passion for gaming and understanding player behaviour.