Staff Data Scientist - Experimentation

Apple Inc

Quick summary

Work type: On-site
Location: San Francisco, CA
Salary: $181,100–$318,400 / yr
Posted: 56 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $162k

This role $250k

$73k most similar roles pay here $345k

This role pays more than 94% of similar roles. Most pay $126,800–$197,133 — 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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Staff Data Scientist - Experimentation

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Join our Ads Experimentation team as a Staff Data Scientist where you will design and build a cutting-edge experimentation platform for Apple's advertising solutions. This hands-on role involves applying advanced statistical techniques, such as causal inference and machine learning, to conduct rigorous analyses and measure the impact of new features on user engagement and advertiser value. You will collaborate with data scientists and engineers to develop scalable tools that facilitate quick decision-making while adhering to privacy commitments. Key responsibilities include designing controlled experiments, providing technical guidance on experiment methodologies, and leading the development of robust data pipelines using SQL, Python, PySpark, or Scala. Ideal candidates have 8+ years of experience in software engineering and data science with expertise in causal inference and A/B testing infrastructure. This role demands strong analytical skills, excellent communication, and a passion for working in a fast-paced environment to drive innovation and improve user experiences globally.

Skills

Python SQL Pyspark Scala A/B testing Causal inference Regression analysis Propensity score matching Difference in differences Regression discontinuity Instrumental variables Data pipelines Data quality checks Monitoring systems Data lineage tracking CI/CD

What you'll do

Design and build a new generation of experimentation platform for ads.
Conduct rigorous analyses using SQL, Python, and statistical methods to improve treatment effect estimates.
Provide expert technical guidance on statistical techniques and experiment design.
Lead the development and maintenance of scalable data pipelines with robust quality checks.
Work directly with stakeholders to identify and prioritize high-impact analytical questions.
Design controlled experiments or counterfactual causal inference studies to estimate intervention impacts.

What we're looking for

- 8+ years of experience in software engineering, data science, or statistics with expertise in SQL and causal inference.
- Conduct rigorous analyses using SQL, Python, and statistical methods to improve treatment effect estimates and design experiments.
- Experience with A/B testing infrastructure, randomized control trials, and marketplace experimentation methodologies.
- Proficiency in causal machine learning tools, observational causal techniques, and data engineering practices.
- Design and maintain scalable data pipelines for automated experiment reporting at scale.
- Strong communication skills to work effectively with senior stakeholders on high-impact analytical projects.

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