Sr. Data Scientist, Apple Services Engineering

Would you like to drive the future of Apple's products, applications, and platform while having the unique opportunity to impact some of the most far-reaching software in the world? The Apple Services Engineering (ASE) organization owns the development and innovation on Apple's cloud-centric products and experiences for users all over the world, including iCloud+, Photos, Mail, Messages, FaceTime, Calendar, Notes, etc. We are the foundation on which Apple's software developers build the products that our customers love. Our multi-disciplinary data team plays a fundamental role in this mission by partnering closely with product, engineering, and business teams to develop a culture of leveraging data to inform and shape our strategy.

Key Qualifications

• 5+ years in an analytics or data science role

• You think about data in terms of statistical distributions and have a big enough analytics toolbox (e.g. Statistics, Machine Learning) to know how to find patterns in data, identify targets for performance, and identify sources of variance about those targets.

• You use good judgment balancing art and science when visually communicating information (e.g. Tableau, Superset, ggplot).

• You have engineered information out of massive and complex datasets (e.g. Hive, Spark, Druid).

• You have proven experience in SQL and at least one programming language (e.g. Python, R, Scala) and are comfortable developing code in a team environment (e.g. git, notebooks, testing).

• You are self-motivated and curious with demonstrated creative and critical thinking capabilities and an innate drive to improve how things work.

• You have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.

• You have excellent verbal and written communications skills and experience in influencing decisions with information.

Description

We are looking for people with a track record in building insights and relationships to affect decisions. This role works on an embedded basis with product teams across ASE. Work includes:

• Communicate with and advocate to a wide audience of engineers, managers and executives to inform decisions.

• Collaborate with stakeholders and Data Engineering to define metrics that we will measure our efforts against as well as defining the instrumentation required for yielding sufficient data.

• Extract information from structured and unstructured data.

• Perform exploratory data analyses and use statistics or machine learning techniques to identify key areas of opportunity and new questions to pursue.

• Plan, design, analyze A/B tests or experiment results.

• Build models to forecast growth, capacity requirements, etc.

• Work with Analytics Engineering to build analytic, visualization, and other information products with a drive to automate and scale the insights available to science and engineering teams.

Education & Experience

• Your academic background is in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, Physics, and etc. Advanced degree preferred.

Pay & Benefits

• At 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 $160,700.00 and $282,500.00, 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.