Senior Data Scientist, Experimentation & Causal Inference

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $181,100–$318,400 / yr
Posted: today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $162k

This role $250k

$85k most similar roles pay here $343k

This role pays more than 95% of similar roles. Most pay $127,703–$195,670 — the shaded band above. At the midpoint, this role pays about $250k versus about $162k 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 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Senior Data Scientist, Experimentation & Causal Inference

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As a Senior Data Scientist specializing in Experimentation and Causal Inference at Apple, you will join the Machine Learning and AI team to enhance the scientific rigor of measurement and decision-making across Apple Services. Your role involves defining experiment methodologies, establishing statistical standards, and generating causal evidence that drives organizational learning. You will collaborate with product, engineering, and data teams to develop advanced causal modeling techniques, build experimentation intelligence systems, and ensure reliable evidence generation for complex AI-powered experiences. Essential skills include expertise in experimental design, causal inference, and modern machine learning methods like uplift modeling and Bayesian experimentation, along with strong programming abilities in Python or R. This role demands a Master's degree or higher in a quantitative field and at least five years of experience in large-scale experiment analysis, complemented by deep knowledge of statistical governance and cross-experiment learning systems.

Skills

Python R Causal Inference Experimental Design Statistical Modeling Machine Learning Bayesian Experimentation Uplift Modeling Meta-Analysis CI/CD

What you'll do

Design and implement advanced causal modeling techniques for complex product behaviors.
Develop and enforce statistical governance standards for experiment readiness across teams.
Create reusable scientific knowledge through experimentation intelligence systems and meta-analysis.
Establish and evolve experimentation methodologies to evaluate AI-powered experiences and intelligent systems.
Define measurement frameworks and KPIs to improve organizational decision-making quality.

What we're looking for

Master's degree or higher in a quantitative discipline like Statistics or Data Science.
5+ years of experience designing and analyzing large-scale experiments or causal analyses.
Deep expertise in experimental design, statistical inference, and causal inference methodologies.
Strong programming skills in Python and/or R for data analysis.
Ability to evaluate experiment validity issues and ensure robust measurement strategies.
Experience developing measurement plans, KPI frameworks, and success criteria for experiments.

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