Staff Data Scientist - Experimentation

Apple Inc

Quick summary

Work type: On-site
Location: San Francisco, CA
Salary: $181,100–$318,400 / yr
Posted: 31 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $172k

This role $250k

$104k most similar roles pay here $341k

This role pays more than 89% of similar roles. Most pay $126,800–$217,725 — the shaded band above. At the midpoint, this role pays about $250k versus about $172k 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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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View all roles at Apple Inc

At a glance

TL;DR · Staff Data Scientist - Experimentation

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As a Staff Data Scientist at Apple's Advertising Platforms group, you will join a dynamic Ads Experimentation team to develop and support cutting-edge experimentation platforms that enable data-driven decision-making while upholding user privacy. Your responsibilities include designing experiments, applying statistical methods, and collaborating with cross-functional teams to ensure seamless integration of new features. You will leverage SQL, Python, Pyspark, and Scala to conduct rigorous analyses, build scalable data pipelines, and create intuitive dashboards for experiment reporting. With a focus on causal inference and A/B testing methodologies, you will provide technical guidance to engineers and scientists, ensuring robust data quality and reliability. This role requires expertise in marketplace dynamics, observational causal techniques, and the ability to communicate complex findings effectively to senior leadership.

Skills

Python SQL Pyspark Scala R 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 AWS Kubernetes

What you'll do

Design and build a new generation of experimentation platform for ads using leading-edge technologies.
Conduct rigorous analyses to uncover insights and improve treatment effect estimates using SQL, Python, and statistical methods.
Provide expert technical guidance on statistical techniques, experiment design, and data engineering to cross-functional teams.
Lead the development and maintenance of scalable and reliable data pipelines with robust quality checks and monitoring systems.
Collaborate with stakeholders to identify high-impact questions and prioritize them for experimentation and analysis.
Design controlled experiments or causal inference studies to estimate the long-term impact of interventions on advertiser value.

What we're looking for

8+ years of experience in software engineering, data science, or statistics with expertise in SQL and causal inference.
Design and conduct controlled experiments using A/B testing methodologies and advanced statistical techniques for accurate treatment effect estimation.
Develop and maintain scalable data pipelines and automate experiment reporting using Pyspark, Scala, or similar technologies.
Provide technical guidance on statistical methods and experiment design to cross-functional teams and senior leadership.
Analyze complex business problems through rigorous end-to-end analyses and communicate clear takeaways that drive actionable decisions.
Familiarity with causal machine learning tools and observational causal techniques such as regression discontinuity and instrumental variables.

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