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.
As a Staff Data Scientist at the Ads Experimentation team, you will play a pivotal role in developing and supporting an advanced experimentation platform for Apple's advertising solutions. Your responsibilities include designing rigorous experiments to measure performance, applying statistical methods to ensure data-driven decision-making, and building scalable tools that enhance quick and accurate analysis. You will work closely with stakeholders and data scientists to create innovative solutions that align with Apple’s privacy standards while connecting users and advertisers effectively. The ideal candidate possesses extensive experience in software development, data science, and statistics, with expertise in SQL, Python, and causal inference techniques such as regression discontinuity and instrumental variables. Familiarity with A/B testing infrastructure and observational causal methods is crucial, along with proficiency in Pyspark or Scala for large-scale data analysis and pipeline development. This role demands a strategic mindset to tackle complex business challenges and mentor junior team members while fostering best practices in data engineering and quality assurance.
Design and build a new generation of experimentation platform for Ads Platform.
Apply leading-edge technologies to enable safe and data-driven feature launches.
Provide expert technical guidance on statistical techniques and experiment design.
Conduct rigorous analyses using SQL, Python, and statistical methods to uncover insights.
Lead the development and maintenance of scalable and reliable data pipelines.
Work with stakeholders to identify and prioritize high-impact analytical questions.
What we're looking for
At least 8 years of experience in software engineering, data science, or statistics with expertise in SQL and causal inference.
Design and analyze controlled experiments using A/B testing methodologies and observational causal techniques like regression discontinuity and instrumental variables.
Develop and maintain scalable data pipelines using Pyspark or Scala for automated experiment reporting at scale.
Provide technical guidance on statistical methods and experiment design to engineers and scientists within the organization.
Conduct rigorous end-to-end analyses to uncover insights, improve treatment effect estimates, and measure advertiser value from campaigns.
Collaborate with senior stakeholders to identify high-impact questions and drive data-driven decision-making.