Applied Data Scientist Unit Economics Understanding San Francisco
Classified Tasks (12)
Augment (9)
AI assists, human decides
Lead development of causal inference and data science models and frameworks to predict and quantify drivers of customer lifetime value (LTV)
leadership
Build causal inference and predictive analytics capabilities to measure and forecast LTV across B2C and B2B customer segments
technical
Quantify the incremental impact of product actions or features on customer LTV
analytical
Design customer “happy paths” by identifying adoption journeys that maximize lifetime value and ensure customers derive maximum value from the ecosystem
creative
Analyze price elasticity to inform product packaging, monetization, and pricing strategies
analytical
Develop and maintain LTV models across product lines and customer cohorts
technical
Architect scalable frameworks and models that democratize economic insights for leadership and functional teams
technical
Support strategic pricing and investment decisions with robust analytical and causal evidence
analytical
Guide sustainable growth by applying unit economics models and frameworks to inform strategic planning
analytical
Human-Only (3)
Requires human judgment
Translate deep data insights into strategic decisions and growth levers for leadership
communication
Partner with Finance, Product, Data Engineering, GTM, and other data science teams to build causal and predictive models that drive business decisions
operational
Lead cross-functional data science initiatives, ensuring analytical rigor, clarity, and timely delivery
leadership