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Role Number: 200666451-0836
Summary
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 & Simulation to help quantify the future impact of strategic decisions under uncertainty.
This 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.
As 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.
The 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.
Description
As a Senior Data Scientist, Strategic Modeling & Simulation, you will develop simulation systems and strategic modeling frameworks that estimate the long-term impact of product, growth, and business decisions.
You 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.
This 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.
The ideal candidate possesses strong technical depth, excellent scientific reasoning skills, and the ability to communicate quantitative insights to executive audiences.
Minimum Qualifications
Master’s degree or higher in Statistics, Data Science, Computer Science, Operations Research, Economics, Applied Mathematics, Industrial Engineering, or a related quantitative discipline.
5+ years of experience in predictive modeling, simulation, forecasting, quantitative strategy, product science, applied economics, operations research, or related fields.
Strong expertise in statistical modeling, machine learning, predictive analytics, forecasting, and quantitative reasoning.
Experience building predictive models such as retention, churn, conversion, engagement, or lifetime value models.
Experience with simulation, scenario analysis, impact estimation, strategic modeling, or long-term value estimation.
Strong Python programming skills and experience with modern machine learning or statistical modeling ecosystems.
Ability to work with large-scale behavioral, product, business, survey, or experimentation datasets.
Strong communication skills and ability to translate complex quantitative modeling outputs into clear decision guidance for leadership audiences.
Preferred Qualifications
PhD in Statistics, Computer Science, Economics, Operations Research, Data Science, Applied Mathematics, Industrial Engineering, or a related quantitative discipline.
Experience with simulation systems, probabilistic modeling, Bayesian methods, survival analysis, causal impact modeling, reinforcement learning concepts, or uncertainty quantification
Experience estimating long-term business impact, investment ROI, subscriber growth, retention compounding, or customer lifetime value.
Experience in Product Science, Applied Economics, Operations Research, Quantitative Research, Strategic Modeling, Decision Science, or related quantitative strategy functions
Experience building strategic modeling systems that combine experimentation evidence, predictive ML, behavioral signals, and business outcomes.
Experience modeling the impact of machine learning systems, recommendation systems, adaptive products, AI-powered experiences, or other complex adaptive systems
Publications or research contributions in venues such as KDD, CIKM, ICML, NeurIPS, WWW, WSDM, RecSys, AISTATS, or related conferences and journals.
Experience supporting executive-level strategic planning, portfolio prioritization, or investment decision-making.
