This role pays more than
95%
of similar roles. Most pay
$129,302–$202,012
— the shaded band above.
At the midpoint, this role pays about
$255k
versus about
$166k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
The Senior Data Scientist, Strategic Modeling & Simulation joins a team focused on quantifying the future impact of strategic decisions under uncertainty. This role involves building simulation systems and modeling frameworks to estimate long-term outcomes for product growth, engagement, retention, and revenue. The individual will develop predictive machine learning models, probabilistic forecasting tools, and scenario analyses to evaluate trade-offs in resource allocation and investment planning. Key responsibilities include linking short-term experimentation signals to long-term business metrics and modeling the impact of emerging technologies like AI-powered experiences and recommendation systems. Required skills include Python programming, statistical modeling, and expertise in machine learning, operations research, and economics. The role addresses complex problems regarding how new products and adaptive systems influence customer behavior and business sustainability across various product, marketing, and engineering domains.
What does a Data Scientist earn in California?
Median $208978 from 66 postings across 27 companies.
Develop simulation frameworks to estimate future product, growth, and revenue outcomes under various strategic scenarios.
Build predictive machine learning models for retention, churn, engagement, and customer lifetime value.
Create impact estimation models to quantify the ROI of features, roadmap initiatives, and engineering investments.
Design probabilistic forecasting methods to represent uncertainty, confidence ranges, and sensitivity to key assumptions.
Develop quantitative approaches for portfolio planning, resource allocation, and trade-off analysis.
Model the long-term impacts of emerging technologies, including AI-powered experiences and recommendation systems.
Link short-term experimentation results and behavioral signals to long-term business metrics and growth.
Translate complex quantitative modeling outputs into clear decision guidance for executive leadership.
What we're looking for
Master's degree or higher in Statistics, Data Science, Computer Science, Operations Research, Economics, Applied Mathematics, Industrial Engineering, or a related quantitative discipline.
PhD in Statistics, Computer Science, Economics, Operations Research, Data Science, 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.
Expertise in statistical modeling, machine learning, predictive analytics, forecasting, and quantitative reasoning.
Experience building predictive models for retention, churn, conversion, engagement, or lifetime value.
Experience with simulation, scenario analysis, impact estimation, strategic modeling, or long-term value estimation.
Proficiency in Python programming and experience with modern machine learning or statistical modeling ecosystems.
Ability to translate complex quantitative modeling outputs into clear decision guidance for leadership audiences.