Data Scientist

Key Skills

Data Analysis, Data science techniques, Data Visualization, Machine learning techniques, NumPy, Object-Oriented programming (OO languages), OOPS, Pandas, Python Programming, Scikit-learn, SciPy

Job Description

Do you want to impact billions of users by developing an extraordinary product with a prime focus on improving hardware performance? You will become part of a hands-on development team that furthers engineering precision, creativity, and innovation. Dynamic, inspiring people and innovative technologies are the norm here. We want you to join our team as a resourceful engineer or data scientist with the desire to research and develop solutions that do not yet exist. Bring passion and dedication to your job and there's no telling what you could accomplish. You will have the opportunity to give to the design and validation of hardware systems across Apple’s newest products including iPhones, Watches, iPads, and others. You will facilitate our understanding of system performance by applying data visualization and analytics techniques to influence hardware design decisions. The role requires a good understanding of statistics, data analytics, and preferably exposure to machine learning concepts. Come join an amazing team at the intersection of hardware and software that uses engineering insights to make the best decisions possible.

Key Qualifications

• You are humble, curious, excited to solve problems, and eager to have a growth mindset
• 3+ years of relevant industry work experience in data-driven projects with a well-rounded understanding of statistical fundamentals learning
• Proficiency with Python and data science libraries (Pandas, NumPy, SciPy, Scikit-Learn, etc.)
• Experience producing significant visualizations/dashboards/presentations to cross-functional teams
• Understanding and exposure to the different levels of the data science cycle (definition, collection, preparation, extraction, analysis, modeling, and deployment)
• Experience with Object Oriented Programming (OOP) concepts & scalable software design principles

Description

In this role you will apply your knowledge of data science, analyze data patterns, interpret trends on different types of data, and use statistical inference to gain real-time insights that could impact our design and validation of hardware systems across multiple Apple products. As a data scientist, you will collaborate with a diverse group of engineers to build custom algorithms as needed; you will develop dashboards, scalable data visualization tools and use machine learning algorithms (classification, clustering, etc.) to answer complex questions and clearly communicate findings to non-technical audiences and cross-functional teams.

Education & Experience

BS or MS in Statistics, Data Mining, Machine Learning, Analytics, Applied Mathematics, Computer Science or related fields required.

Additional Requirements

• Passion for Hardware Product Design using data analysis
• Experience with Machine Learning projects

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 $125,800 and $229,400, 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.