Senior Data Analyst (LTV) in London

Minute Media is a leading global sports content and technology company. We create authentic stories from diverse perspectives across our portfolio of content brands, which include Sports Illustrated, 90min and FanSided. We are looking for a data-driven Data Analyst specializing in LTV (Lifetime Value) & Subscriptions to join our London team. You will support all analytics related to our subscription products and user lifecycle. In this role, you will dive deep into subscriber behavior and churn patterns, develop models to project customer lifetime value, and help drive strategies to improve retention. You’ll work closely with our Growth, Product, and Editorial teams to ensure data-driven decision-making in areas like paywall optimization, subscriber engagement, and content strategy for member audiences. This is a mid-level, full-time, hybrid on-site role ideal for someone passionate about using data to fuel audience growth and loyalty.

Responsibilities

• Analyze the subscription funnel end to end, tracking users from anonymous visitors to registered users and paying subscribers in order to identify drop-off points, conversion bottlenecks, and opportunities to improve sign-up rates.
• Monitor key subscription and user engagement metrics through daily, weekly, and monthly dashboards, and own analysis of metric changes over time.
• Perform deep-dive analyses on user retention.
• Present user insights to stakeholders by clearly identifying our most valuable users and what drives their engagement, and go beyond reporting by recommending concrete next steps to inform content and marketing decisions.

LTV & Churn Modeling

• Develop and maintain subscriber Lifetime Value (LTV) models, continuously refining them by incorporating new data to improve accuracy.
• Build and improve churn prediction models to proactively identify at-risk subscribers, using statistical or machine learning techniques as needed.
• Work with large subscription and engagement datasets to calculate LTV and churn while accounting for promotional pricing, seasonality, and content engagement.
• Translate model outputs into clear, actionable business recommendations.

Cross-Functional Collaboration

• Collaborate with Growth and Marketing teams to define success measurement plans for initiatives.
• Work closely with Product Managers and Engineers to ensure user interaction data is accurately captured and available in the data warehouse, and advocate for new data collection where it would improve LTV or churn analysis.
• Partner with data and product teams to uncover trends in subscription behavior, including content engagement and the impact of new features on loyalty.
• Communicate insights and recommendations clearly to both technical and non-technical audiences, tailoring depth and format to drive understanding and action.

Requirements

• You have 5+ years of experience in data analysis or data science, with a focus on user lifecycle, customer analytics, or subscription metrics.
• You bring advanced SQL skills and are comfortable querying and manipulating large datasets in a cloud data warehouse environment.
• You have experience building and maintaining data pipelines or intermediate data models, transforming raw event logs into aggregated, analysis-ready datasets for high-performance reporting.
• You have worked with BI and data visualization tools, ideally Looker Studio, to build dashboards and reports that track KPIs over time.
• You are familiar with statistical analysis and predictive modeling concepts such as cohort analysis, regression, survival analysis, experimentation, and churn prediction, even if you are not a dedicated data scientist.
• You demonstrate strong problem-solving skills and attention to detail, with the ability to validate data integrity, spot anomalies, and ensure accurate calculation of metrics like LTV.
• You understand experimental design in product or marketing contexts, including defining success metrics, determining sample sizes, and evaluating statistical significance.
• You communicate complex analytical findings clearly and make data-driven recommendations.
• You work effectively across functions and manage multiple priorities in a dynamic environment.
• You hold a B.Sc./B.A. in Statistics, Economics, Business, Computer Science, or a related field, or equivalent practical experience.

Advantageous

• Previous experience in subscription-based digital media or a similar industry (e.g., streaming services, membership products) where you’ve worked on subscriber analytics.
• Hands-on experience with subscription management or CRM platforms (such as Piano, Zuora, Stripe, or Salesforce Marketing Cloud) – understanding their data structures and how to extract meaningful insights from them.
• Knowledge of customer segmentation and personalization strategies, possibly using CDP (Customer Data Platform) tools like BlueConic.
• Programming skills in Python or R for advanced data analysis or to implement custom predictive models beyond basic SQL (e.g., using libraries for churn modeling or LTV projections).
• Experience analyzing web/app user behavior using tools like Google Analytics or Mixpanel, especially if related to funnel analysis or retention tracking.
• A passion for sports and familiarity with Minute Media’s content – understanding our audience’s interests can help in crafting more relevant insights.

What You’ll Get

• Opportunity to make a meaningful impact in a fast-growing company.
• Career development opportunities & different skill-based workshops offered each quarter.
• Central London based office.
• Hybrid work model.
• Cycle to Work scheme.
• Hybrid vacation model.
• Extended parental leave.
• Private Health Insurance including mental health, dental and optical cover.
• Standard access to WellHub with options to upgrade to premium membership.
• Fun company events and celebrations with a focus on DEI each quarter.
• Community involvement opportunities, both in-person and remote.

Minute Media is committed to creating a diverse and inclusive work environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.