Business Intelligence Analyst

Fortune Media•New York City, NY

6d•$60 - $110

About The Position

The Business Intelligence Analyst will own critical analytics used to drive subscription growth, retention, and revenue optimization. This role partners closely with Marketing, Product, and Finance to turn complex subscriber, traffic, and revenue data into clear, actionable insights that inform strategy and day-to-day decision making.

Requirements

Proven experience in a Business Intelligence, Analytics, or Data Science role supporting a subscription, digital media, or e-commerce business.
Deep hands-on experience with cohort-based retention analysis, including interpreting the impact of pricing and value proposition changes on retention and revenue.
Demonstrated ability to design and implement LTV methodologies (top-down and/or bottom-up) that support forecasting, offer testing, and portfolio optimization.
Deep experience with subscription revenue forecasting and budget planning, including the ability to model how different offer types, billing cadences, and promotional structures affect recognized revenue over time.
Proficiency with a BI/visualization tool (e.g., Looker, Tableau, Power BI, Mode) to build dashboards and self-service reporting for non-technical stakeholders.
Ability to translate ambiguous business questions into concrete analytical plans, including defining metrics, cohorts, and success criteria.
Strong communication skills, including experience presenting findings and recommendations to cross-functional stakeholders and leadership.

Nice To Haves

Experience with subscription analytics in publishing, news, or digital magazines (e.g., paywall funnels, trial optimization, cross-platform engagement).
Understanding of digital advertising and marketing attribution, with specific experience analyzing performance by traffic source, referrer, and campaign over time.
Familiarity with customer data and marketing platforms (e.g., Salesforce Marketing Cloud, Iterable, Piano, Recurly, or similar tools).
Knowledge of statistical methods for experiment design and analysis (A/B testing, incrementality, causal inference).
Experience working with customer journey/event data for funnel analysis, churn modeling, or personalization.
Comfort with a scripting language (e.g., Python or R) for more advanced modeling or automation.

Responsibilities

Support subscription revenue forecasting and budget modeling, including analysis of how offer mix across monthly, annual, trial, discount, and promotional plans impacts recognized revenue, cash flow timing, and long-range revenue planning.
Build and maintain retention analyses by cohort to understand the impact of value propositions and pricing changes on subscriber retention and revenue over time.
Develop and operationalize lifetime value (LTV) models for current and new subscription offers, including the ability to size new offers using a retention model and projected LTVs.
Analyze advertising revenue by cohort and traffic referrer to illuminate how different acquisition sources and campaigns perform over the customer lifecycle.
Create, QA, and document logic for key funnel and behavioral metrics, ensuring all stakeholder teams can reliably use and interpret the outputs.
Partner with lifecycle, growth, and product teams to translate business questions into clearly defined analytical requirements, then deliver dashboards, reports, and presentations that drive decisions.
Partner with data engineering to define requirements for consistent user identifiers, event taxonomies, and attribution rules, and then validate that these data sets support the analytics use cases above.
Proactively identify data quality issues, define remediation approaches, and advocate for improvements that increase trust in BI outputs.
Communicate complex analytical findings in simple, non-technical language, including recommended actions and expected business impact.