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Apple Inc.

AIML Senior Data Scientist, Experimentation

Apple Inc., Jackson, Mississippi, United States,


Seattle, Washington, United StatesMachine Learning and AIWe are looking for an experienced data scientist to build experimentation platforms to empower Apple engineers in delivering great user experiences. We are addressing key challenges to accelerate the adoption of ML across all the OSes and Apple products/services operating at the scale of 2+ billion devices. Our work is complex, challenging and highly visible. Collaborate with OS, data, and full-stack engineers to build data products that provide reliable and timely insights for Apple's applications & services.DescriptionYou'll be responsible for enhancing the experimentation platform with statistical tools & techniques that will be used by all teams across Apple. You'll partner with these teams to drive experiment automation & methodology improvements. For example, build data service to analyze telemetry from billions of devices in a timely fashion and deliver data-driven insights to inform product launches. In this role, you will collaborate with cross-functional partners and customers across Apple to build platform roadmap for next 2-3 years. You have a background that fuses data science, engineering, and product thinking. You have years of practical experience building measurement, evaluation, and insights to improve products.Minimum QualificationsAt least 5 years of experience in statistical / machine learning theory & applications, in particular with experimentation techniquesExperience designing, building, and shipping productsAbility to tell stories with data & educate teams effectively to act on recommendationsHands-on experience with managing and monitoring data collection and analytics pipelines at the application levelExperience with object-oriented programming languages like Scala / PythonExperience with SQL / NoSQL databasesKey QualificationsPreferred QualificationsAt least 8 years of experience in statistical / machine learning theory & applications, in particular with experimentation techniquesExperience designing, building, and shipping productsAbility to tell stories with data & educate teams effectively to act on recommendationsHands-on experience with managing and monitoring data collection and analytics pipelines at the application levelExperience with object-oriented programming languages like Scala / PythonExperience in building large scale data science pipelines and distributed systems using technologies like Spark/Kafka/HiveExperience with SQL / NoSQL databasesMS/PhD (or equivalent) in CS/data Science/mathematics/statistics or other scientific fieldsAdditional RequirementsAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,600 and $296,300, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

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