Senior Data Scientist, Strategic Modeling & Simulation

At Apple many of the most consequential decisions are made long before products launch features ship or investments are approved. We are seeking a Senior Data Scientist StrategicModeling u0026 Simulation to help quantify the future impact of strategic decisions under uncertainty. nnThis role combines strategic simulation predictive modeling machine learning impact estimation forecasting and quantitative decision science to help leadership evaluate opportunities understand trade-offs and make better long-term investment decisions. You will develop the models that connect experimentation learnings behavioral signals and business outcomes into forward-looking simulations that support strategic planning and resource allocation. nnAs Apple expands investments in AI-powered experiences and intelligent systems this role will help assess the long-term implications of emerging technologies and evolving customer behaviors while supporting strategic decision-making under uncertainty. nnThe ideal candidate combines strong quantitative rigor with systems thinking scientific curiosity and a passion for solving complex product and business problems through modeling and simulation.

As a Senior Data Scientist Strategic Modeling u0026 Simulation you will develop simulation systems and strategic modeling frameworks that estimate the long-term impact of product growth and business decisions. nnYou will work across experimentation product marketing consumer research engineering finance and leadership teams to develop predictive models impact estimation frameworks and strategic scenario simulations that support decision-making under uncertainty. nnThis role sits at the intersection of machine learning economics forecasting simulation operations research and quantitative strategy. You will help develop forecasting and simulation capabilities that support both traditional product investments and emerging technology initiatives where long-term outcomes are uncertain and difficult to measure directly. nnThe ideal candidate possesses strong technical depth excellent scientific reasoning skills and the ability to communicate quantitative insights to executive audiences.

Strategic Simulation: Develop simulation frameworks that estimate future product growth subscriber engagement retention and revenue outcomes under alternative strategic Investment Modeling: Build product investment simulations that estimate the long-term impact of proposed features roadmap initiatives and engineering investments before resources are Modeling u0026 Opportunity Sizing: Estimate the impact of product growth and operational investments including conversion elasticity feature ROI subscriber growth retention lift and revenue Machine Learning: Develop predictive models for retention churn engagement subscriber growth conversion lifetime value and behavioral outcomes that serve as in puts into simulations and strategic -Term to Long-Term Metric Linkage: Build models that connect short-termexperimentation outcomes and behavioral signals to long-term retention monetization subscriber growth and customer lifetime Forecasting u0026 Uncertainty Quantification: Develop forecasting and probabilistic modeling approaches that represent uncertainty confidence ranges scenario distributions and sensitivity to u0026 Resource Allocation: Develop quantitative approaches for portfolio planning resource allocation initiative prioritization and constrained investment trade-off Scenario Analysis: Evaluate trade-offs across competing strategic initiatives and communicate expected outcomes risk ranges assumptions and decision Technology Impact Modeling: Develop frameworks that estimate the potential long-term impact of new technologies AI-powered experiences recommendation systems and adaptive products on engagement retention subscriber growth and business -Functional Collaboration: Partner with Product Marketing Experimentation Science Consumer Research Engineering Finance and leadership teams to support strategic planning and investment decisions.

Masters degree or higher in Statistics Data Science Computer Science Operations Research Economics Applied Mathematics Industrial Engineering or a related quantitative discipline.n5 years of experience in predictive modeling simulation forecasting quantitative strategy product science applied economics operations research or related expertise in statistical modeling machine learning predictive analytics forecasting and quantitative building predictive models such as retention churn conversion engagement or lifetime value with simulation scenario analysis impact estimation strategic modeling or long-term value Python programming skills and experience with modern machine learning or statistical modeling to work with large-scale behavioral product business survey or experimentation communication skills and ability to translate complex quantitative modeling outputs into clear decision guidance for leadership audiences.

PhD in Statistics Computer Science Economics Operations Research Data Science Applied Mathematics Industrial Engineering or a related quantitative with simulation systems probabilistic modeling Bayesian methods survival analysis causal impact modeling reinforcement learning concepts or uncertainty quantificationnExperience estimating long-term business impact investment ROI subscriber growth retention compounding or customer lifetime in Product Science Applied Economics Operations Research Quantitative Research Strategic Modeling Decision Science or related quantitative strategy functionsnExperience building strategic modeling systems that combine experimentation evidence predictive ML behavioral signals and business modeling the impact of machine learning systems recommendation systems adaptive products AI-powered experiences or other complex adaptive systemsnPublications or research contributions in venues such as KDD CIKM ICML NeurIPS WWW WSDM RecSys AISTATS or related conferences and supporting executive-level strategic planning portfolio prioritization or investment decision-making.