Biostatistician - Health

At Apple, we build technology that helps people understand their health and act on it. The Health & Fitness team designs and executes the clinical research behind features that reach hundreds of millions of people — atrial fibrillation detection, hypertension, sleep apnea, and the next generation of health sensing.

We are looking for a Biostatistician who wants their statistical work to end up in someone's pocket rather than only in a journal. In this role, you own the statistical strategy and execution for studies end-to-end: you help shape the questions, help design the studies that can answer them, defend the analyses to regulators, and translate the results for engineers, clinicians, and product teams. You will work with engineering study leads, clinical scientists, regulatory affairs, and external principal investigators.

This is a role for someone who is equally comfortable arguing about an endpoint definition with a cardiologist and about a data pipeline with an engineer. If you care about scientific integrity, and about doing rigorous work at a scale very few organizations can offer, we would like to hear from you.

You will serve as the statistical DRI for clinical studies within Apple Health, partnering closely with engineering study leads and clinical scientists to take features from concept through clinical validation and submission. You are accountable for the statistical rigor of study design, analysis, and reporting, and for the integrity of the data that supports our health claims. You will also help build the durable processes — data strategy, study templates, analysis standards — that let the team move faster on every study that follows.

Minimum Qualifications

PhD or Master's degree in biostatistics, statistics, biomedical engineering, epidemiology, public health, or a closely related quantitative field.
Working proficiency in a statistical programming language such as R, Python, or SAS, including experience working with or building statistical infrastructure or standards (i.e. reproducible analysis pipelines, validated programs, or reusable analysis functions or templates).
Demonstrated experience authoring clinical study documentation including statistical analysis plans and clinical study reports.
Familiarity with strengths and limitations of frequentist and Bayesian methods, adaptive designs, or real-world evidence approaches.
Practical knowledge of GCP and the regulatory framework governing clinical investigations of medical devices.
Demonstrated ability to bridge discussions between engineering and clinical experts.

Preferred Qualifications

Therapeutic expertise in cardiology, women's health, or neurology.
Established track record designing and executing clinical trials.
Experience with diagnostic accuracy and agreement studies: sensitivity and specificity, positive predictive value, ROC analysis, and reader adjudication designs.
Experience analyzing wearable, sensor, or other high-frequency longitudinal data, including handling of intermittent measurement and informative missingness.
Strong scientific communication record: peer-reviewed publications, regulatory documents, and presentations to clinical and executive audiences.
Experience with decentralized, remote, or app-based studies operating at large participant scale.