Collaborate with cross-functional teams (Business Engineering Product Finance and Marketing) to define key metrics data requirements and models for analysis experimentation and reporting. Investigate large-scale datasets to identify trends measure impact and generate insights that improve subscription mechanics. Build data products that lead to developer success. Apply statistical methods and build predictive models including LTV and propensity models to support multiple and often interrelated subscription the incremental impact of subscription initiatives using causal inference and testing methodologies. Explore how emerging technologies such as generative AI can be applied to create business value. Partner with teams across Apple to support responsible data collection governance and access.
5 years of experience as a Data Scientist or Analyst in digital media subscription or fintech environments with a proven track record of business measurement and optimization.
Strong proficiency in SQL and at least one programming language such as Python or R; experienced in building analytical datasets and pipelines using large-scale structured and unstructured data.
Applied expertise in statistics probability and experimental techniques including A/B testing regression clustering survival analysis and causal inference.
Demonstrated project ownership with an ability to condense & communicate complex data into clear actionable business insights for cross-functional stakeholders.
Bachelors degree in a quantitative field (e.g. Computer Science Statistics Economics) or equivalent professional experience.
Quantitative expertise in understanding the economics of subscription businesses.
Experience in a digital subscription or large-scale e-commerce business.
Masters in a quantitative field is a plus but not required.
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