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AIML - Senior Data Scientist, Machine Learning Platform and Infrastructure

SummaryPosted: Dec 20, 2024Weekly Hours: 40Role Number:200556588The AI/ML Integration and Delivery team is looking for a experiencedData Scientist. Our organization specializes in CI/CD and the delivery of AI models to servers and customer devices alike. Our team’s mission is to make the engineering workflow as transparent as possible for AIML engineers by providing metrics and engineering UIs. This requires us to produce and aggregate data from many sources, both emanating from our engineering systems and our customers' devices, process it, report it and guarantee its quality and reliability. Something that sets this role apart from typical product DS roles is that it requires a deep interest in complex engineering system and a passion about measuring their efficiency and reliability with data (from our own pipelines all the way to customers' devices).We are looking for a strong data scientist to help us fulfill this mission by collaborating with a global team of data scientists and software engineers.DescriptionDescriptionIn this role, you will be expected to be the face of the metrics team for our external stakeholders owning KPIs end-to-end from definitions, instrumentation design to reporting. You will be expected to build a deep understanding of our overall engineering experience and CI/CD practices, and our data landscape, and bring everything together. You will be the expert of our org’s KPIs and work proactively to improve the usability. You will collaborate closely with Data Scientists, Release engineers, UI Engineers, Backend Engineers and Device Engineers, as well as with senior leadership.The ideal candidate is a highly motivated, collaborative, and proactive individual who can communicate effectively and can adapt and learn quickly.Minimum QualificationsMinimum Qualifications• Expert at translating ambiguous business problems into technical solutions by working with business partners to design, develop and deploy data science solutions that drive key product decisions• Strong programming skills, including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala).• Self-starter, comfortable with ambiguity, and enjoy working in a fast-paced dynamic environment• Experienced in building and maintaining large-scale ETL/ELT pipelines that are optimized for performance and can handle data from various sources, structured or unstructured.• Proven expertise in developing data visualizations & reporting. Ex: Tableau, Superset, Qlickview, etc• Proficiency in data science, machine learning and statistical data analysisKey QualificationsKey QualificationsPreferred QualificationsPreferred Qualifications• >5 years of relevant work experience in Data Science / Analytics• Degree in computer science, economics, business analytics, data science, statistics or related field• * A strong sense of data ownership, being willing to guarantee data quality even if it originates from sources you don’t directly control• * Outstanding ability to communicate, simplify problems, and drive towards a solution• * Ability to thrive in a complex and constantly changing environment.• * Outstanding ability for cross-functional collaboration and driving large-scale projects• Ability to work on both internal data emanating from engineering systems, and very large-scale data emanating from devices• Capacity to translate business requirements into technical solutions.• Experienced in writing and maintaining high-quality code using standard methodologies such as code reviews, unit testing, and continuous integration.• Good time management skills and can incrementally deliver to tight schedules.• (plus but not required) Understanding of ML Processes, Engineering systems, Developer Operations, and Software CI/CDEducation & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsPay & BenefitsPay & 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 $175,800 and $312,200, 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. Learn more about Apple Benefits.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.More• 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. Learn more about your EEO rights as an applicant.
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$244000 / YEARLY (est.)
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$175800K
$312200K

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What You Should Know About AIML - Senior Data Scientist, Machine Learning Platform and Infrastructure, Apple

If you're an experienced Data Scientist looking for an exciting challenge, the AIML - Senior Data Scientist role at Apple in Cupertino, CA, could be your perfect fit! You'll be diving into the fascinating world of AI and machine learning, working on the AI/ML Integration and Delivery team, where your expertise will shape how we deliver AI models across servers and customer devices. This is not just another data job; it’s about making the engineering workflow transparent for AIML engineers. You’ll play a vital role in producing and aggregating data from multiple sources, ensuring the quality and reliability of the metrics you gather and analyze. Being at the forefront of KPI ownership, you’ll need to have a knack for turning complex engineering problems into actionable insights. Your collaboration with a diverse team of data scientists and engineers will be pivotal as you bring your technical skills in SQL, Python, and data visualization tools like Tableau to the table. If you have a passion for data quality and a deep understanding of engineering systems, this role is designed for you. Join Apple, where your contributions will directly enhance our engineering practices and fundamentally impact the user experience of millions around the globe. We’re not just looking for a data expert; we’re seeking a proactive communicator and a keen collaborator who thrives in dynamic environments. Let’s innovate together at Apple where your work truly matters!

Frequently Asked Questions (FAQs) for AIML - Senior Data Scientist, Machine Learning Platform and Infrastructure Role at Apple
What are the key responsibilities of the AIML - Senior Data Scientist role at Apple?

As the AIML - Senior Data Scientist at Apple, you will be responsible for owning key performance indicators (KPIs) end-to-end, from design to reporting. This role requires you to gather and process data from multiple engineering systems, ensuring its quality and reliability. You will collaborate closely with various engineering teams, contributing to the overall efficiency of our AI/ML practices.

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What qualifications are needed for the AIML - Senior Data Scientist position at Apple?

Candidates applying for the AIML - Senior Data Scientist role at Apple should have over 5 years of relevant experience in Data Science or Analytics and possess a strong programming background, specifically in SQL and Python. A degree in fields such as computer science, statistics, or business analytics is preferred, as well as proven experience in building large-scale ETL/ELT pipelines.

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How important is collaboration in the AIML - Senior Data Scientist role at Apple?

Collaboration is essential in the AIML - Senior Data Scientist role at Apple. You will work closely with data scientists, release engineers, and various engineering teams to understand and communicate metrics effectively. Your ability to collaborate will drive large-scale projects and contribute to the overall engineering workflow.

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What technical skills are essential for the AIML - Senior Data Scientist at Apple?

For the AIML - Senior Data Scientist position at Apple, strong technical skills in data-querying using SQL, as well as proficiency in a scripting language like Python, R, or Scala are crucial. Furthermore, experience with data visualization tools such as Tableau or Superset will enhance your ability to communicate insights derived from data.

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What is the expected salary range for the AIML - Senior Data Scientist role at Apple?

The salary for the AIML - Senior Data Scientist role at Apple ranges from $175,800 to $312,200, depending on qualifications, experience, and skills. In addition to base pay, Apple offers a comprehensive benefits package that includes health coverage, stock options, and tuition reimbursement.

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Common Interview Questions for AIML - Senior Data Scientist, Machine Learning Platform and Infrastructure
Can you explain your experience with ETL/ELT pipelines for the AIML - Senior Data Scientist role?

When discussing your experience with ETL/ELT pipelines, be specific about tools you’ve used, such as Apache Spark or AWS Data Pipeline. Highlight any optimizations you made and how you ensured data quality, as those are key components of the AIML - Senior Data Scientist role at Apple.

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How do you approach translating ambiguous business problems into technical solutions?

To effectively translate ambiguous business problems into technical solutions, focus on gathering detailed requirements through discussions with stakeholders, leveraging your analytical skills to clarify objectives, and showcasing past examples where your solutions drove impactful decisions.

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What programming languages are you proficient in, and how have you used them in past projects?

Highlight your proficiency in programming languages relevant to the role, such as Python or R. Discuss specific projects where you utilized these languages for data analysis or to build machine learning models, demonstrating your ability to apply technical knowledge in practical scenarios.

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Describe a time when you collaborated with a team of engineers to deliver a project.

In your response, focus on a specific project where you worked alongside engineers, emphasizing your role, the communication strategies you applied, and how your collaborative efforts led to successful project outcomes, showcasing teamwork and problem-solving skills.

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How do you ensure the quality and reliability of the data you work with?

Explain your systematic approach to data quality, including steps like regular audits, validation checks, and source evaluation. Use examples to illustrate how you’ve identified and rectified data issues in previous roles.

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What data visualization tools have you used, and what is your approach to creating them?

Discuss the data visualization tools you’re experienced with, such as Tableau or Qlikview, and describe your approach to creating visualizations. Emphasize your focus on clarity, storytelling with data, and how you adapt visualizations to meet the needs of different audiences.

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How do you prioritize tasks in a fast-paced and dynamic environment?

Describe your method for prioritizing tasks, such as using project management frameworks or tools, assessing urgency versus importance, and communicating priorities with your team. Illustrate your approach with examples from past experiences where effective prioritization made a difference.

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What experiences do you have with machine learning processes or models?

Share specific experiences where you developed or deployed machine learning models, focusing on the algorithms used, the problems addressed, and how you validated the model’s performance, showing your understanding of ML processes.

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Can you give an example of a project where you added value through data analysis?

Prepare an example of a project where your data analysis led to actionable insights or improvements. Discuss the methodologies used, challenges faced, and the eventual outcome, highlighting your analytical skills and impact on the business.

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How do you continue to develop your skills in data science and machine learning?

Talk about your commitment to lifelong learning in data science. Mention specific courses, certifications, or self-study areas you've pursued recently and how you apply new knowledge to your work, illustrating your proactive approach to skill development.

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CULTURE VALUES
Inclusive & Diverse
Diversity of Opinions
Work/Life Harmony
Dare to be Different
Reward & Recognition
Empathetic
Take Risks
Growth & Learning
Transparent & Candid
Mission Driven
Passion for Exploration
Feedback Forward
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
Learning & Development
Paid Time-Off
Maternity Leave
Social Gatherings
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
December 22, 2024

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