GoodRx is the leading prescription savings platform in the U.S. Trusted by more than 25 million consumers and 750,000 healthcare professionals annually, GoodRx provides access to savings and affordability options for generic and brand-name medications at more than 70,000 pharmacies nationwide, as well as comprehensive healthcare research and information.
Since 2011, GoodRx has helped consumers save nearly $75 billion on the cost of their prescriptions.
Our goal is to help Americans find convenient and affordable healthcare.
We offer solutions for consumers, employers, health plans, and anyone else who shares our desire to provide affordable prescriptions to all Americans.
About The RoleThe Director of Data Analytics – Subscriptions will provide strategic leadership, vision, and execution to drive growth and engagement for subscription products at GoodRx.
This individual will lead a high-performing analytics team, leveraging data to optimize the customer journey, enhance retention, and inform product strategies.
With proven experience in subscription-based businesses, the ideal candidate will partner closely with cross-functional teams, including Product, Design, and Engineering to deliver data-driven insights that shape the future of our subscription offerings.
As a key member of our leadership team, you will have the opportunity to make a significant impact on how we engage with our customers and scale our subscription business.
The ideal candidate has deep experience in subscription analytics within consumer-facing organizations and a strong ability to influence decision-making at the highest levels.
Responsibilities:Develop and execute a comprehensive analytics strategy to support subscription growth, engagement, retention, and overall customer lifecycle optimization.
Build, lead, mentor, and inspire a high-performing team of analysts.
Partner with subscription product, marketing, and engineering teams to define success metrics, establish reporting frameworks, and deliver actionable insights.
Lead the design and implementation of advanced analytics models to understand customer behaviors, predict churn, and optimize pricing and promotions.
Define key performance indicators (KPIs) for subscription performance and implement dashboards and reporting systems to track progress.
Support experimentation (A/B testing) efforts, including test design, analysis, and insights to inform subscription product and marketing strategies.
Identify opportunities to improve the customer experience and drive business outcomes through analytics and data storytelling.
Advocate for a data-driven culture, fostering cross-functional collaboration and ensuring data accuracy, accessibility, and usability across teams.
Communicate complex analyses and recommendations clearly and concisely to stakeholders and senior leadership.
Skills and Qualifications:12-15 years of experience in data analytics, with a strong focus on subscription-based products and business models.
5+ years of experience leading and managing analytics or data science teams.
Proven expertise in subscription lifecycle analytics, including acquisition, engagement, retention, and churn modeling.
Proficiency in SQL, Python, R, or other analytical tools, and experience with data visualization platforms (e.g., Looker, Tableau).
Strategic thinker with a customer-focused mindset and the ability to translate business goals into analytical frameworks and recommendations.
Demonstrated ability to use data to inform and influence product and business decisions.
Strong communication skills with the ability to present insights to technical and non-technical audiences, including executive leadership.
Experience working with cross-functional teams, including product, marketing, and engineering.
Bachelor's degree in Analytics, Statistics, Computer Science, or a related field; advanced degree preferred.
Preferred Qualifications:Experience in subscription businesses within e-commerce, entertainment, or professional services.
3+ years of experience working with healthcare data.
Familiarity with customer segmentation, cohort analysis, and personalization strategies.
Experience in managing data infrastructure and collaborating with engineering teams to ensure robust data pipelines and quality.
Proven track record of driving innovation and implementing advanced analytics techniques, such as machine learning or predictive modeling, to solve business challenges.
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