Senior Data Scientist, Experimentation & Causal Inference

Apple Inc.; Cupertino (CA); Hybrid; USD 185,000 - 325,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Discounted Apple products or services

Tuition reimbursement

Bonuses or commissions

Relocation

Job summary

Apple Inc. is seeking a Senior Data Scientist, Experimentation & Causal Inference to advance measurement, experimentation, and organizational learning at scale.

You will define how success is measured, design experiments, and generate causal evidence across Apple Services, moving beyond traditional A/B testing. The role blends statistics, causal inference, and scientific reasoning to build reusable knowledge and scalable experimentation intelligence.

Qualifications

• Master’s degree or higher in a quantitative field.
• 5+ years designing, analyzing, and interpreting large-scale experiments or causal analyses.
• Strong programming in Python and/or R.
• Experience with measurement plans, KPI frameworks, guardrails, and experiment readiness processes.
• Ability to explain complex statistical concepts and causal claims.

Responsibilities

• Experiment Design & Measurement Strategy.
• Scientific Experiment Design.
• Experiment Readiness & Statistical Governance.
• Causal Inference & Methodology Development.
• Advanced Causal Modeling.
• Cross‑Functional Collaboration.
• Communication & Influence.

Skills

Python

R

Experiment design

Causal inference

Statistical modeling

Power analysis

Measurement strategy

Communication skills

Education

Master's degree or higher in Statistics, Data Science, Biostatistics, Computer Science, Economics, Applied Mathematics, Operations Research, or a related quantitative discipline

PhD in Statistics, Biostatistics, Economics, Computer Science, Data Science, Applied Mathematics, Operations Research, or a related quantitative discipline

Job description

Apple Inc. is seeking a Senior Data Scientist, Experimentation & Causal Inference to advance measurement, experimentation, and organizational learning at scale.

You will define how success is measured, design experiments, and generate causal evidence across Apple Services, moving beyond traditional A/B testing. The role blends statistics, causal inference, and scientific reasoning to build reusable knowledge and scalable experimentation intelligence.