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Senior Data Scientist - Experimentation

Apple New York, NY

New York, NY

Today

$185k - $278k/yr Full time Python Senior A/B Testing

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Job Description

Apple is building the next generation of ads experimentation capabilities, and this role focuses on designing and delivering a new experimentation platform for the Ads Platform organization. As a Senior Data Scientist, you will combine rigorous statistical thinking with scalable data engineering to support privacy-committed, data-driven feature launches that connect Apple users and advertisers.

The position is based in New York, NY (onsite), with a base pay range of USD 184,700 to 277,600 per year. The role requires a minimum of 5 years of relevant experience and an advanced degree in a quantitative field.

What you will do

Design and build a new generation of experimentation platform for the Ads Platform organization.
Use leading-edge technologies to enable safe, data-driven launches while delivering on Apple’s privacy commitment through experimentation.
Partner with stakeholders and data scientists to design experiments and statistical methods that reflect marketplace dynamics and support reliable treatment effects.
Provide technical guidance to engineers and scientists on statistical techniques, experiment design, and data engineering.
Run rigorous, end-to-end analyses using SQL, Python, and statistical methods to uncover insights and improve treatment effect estimates.
Lead the design, development, and maintenance of scalable, reliable data pipelines.
Implement robust data quality checks, monitoring systems, and data lineage tracking.
Advocate best practices for data engineering.
Work directly with stakeholders, including senior leaders, to identify, scope, and prioritize high-impact questions.
Mentor junior engineers and scientists on the team.

Required qualifications

Advanced Degree in Computer Science, Statistics, Applied Math, or a related field.
5+ years of experience in software and data science or statistics, with an in-depth understanding of SQL and causal inference.
Experience in SDLC is preferred.
Direct experience conducting analysis to uncover insights and improve treatment effect estimates using SQL, Python, and statistical methods.
Experience with A/B testing infrastructure and methodologies, including a deep understanding of assumptions behind randomized control trials.
Familiarity with causal machine learning tools and technologies.
Strong grounding in observational causal techniques such as regression, propensity score matching, Diff in Diff, regression discontinuity, and instrumental variables.
Experience designing and analyzing controlled experiments or counterfactual causal inference studies to estimate incremental and long-term intervention impact.
Proficiency in SQL and PySpark or Scala to conduct analyses and build data products such as pipelines and dashboards for automated experiment reporting at scale.
Skilled at operating in a cross-functional organization and working through ambiguous, complex problems to produce clear, actionable takeaways.
Excellent communication, social, and presentation skills.

Tools and technologies

SQL, Python, statistical methods, PySpark, Scala
A/B testing
Causal machine learning tools and technologies
Regression, propensity score matching, Diff in Diff, regression discontinuity, instrumental variables
SDLC, data pipelines, dashboards

Compensation and benefits

Medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments, and relocation (if eligible)
Participation in Apple’s discretionary employee stock programs, including eligible discretionary restricted stock unit awards and eligibility to purchase Apple stock at a discount via the Employee Stock Purchase Plan

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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