채용
Benefits & Perks
•Top Tier compensation with equity
•Wellness benefits
•Remote work flexibility
•Health, dental, and vision coverage
•Learning and development stipend
Required Skills
Apache Spark
SQL
PyTorch
About the Role
Do you get excited by driving product impact via measurement and evaluation, for products and services used by hundreds of millions of people globally? Within the evaluation organization, the mission of Data Science and Insights team is to guide product development, decisions and directions through principled evaluation and rigorous use of data.
You will partner with various engineering teams to improve search quality and guide feature development with data, to deliver amazing search experiences across i Phone, i Pad, Home Pod, Mac, Watch, tv, across dozens of languages.
Responsibilities
- Research and develop evaluation methods to improve the quality of Siri's user facing products
- Work with evaluation/experimentation engineering teams to get your methodological developments translated into technologies that Siri engineering will use every day
- Work with large, complex data sets and solve difficult, non-routine analysis problems, applying advanced analytical methods as needed
- Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing work, and presentations
- Build and prototype analysis pipelines iteratively to provide insights at scale
- Develop comprehensive knowledge of Siri Search data structures and metrics, advocating for changes where needed for product development
- Partner closely with Siri search engineering teams on core machine learning algorithms and systems that are part of Siri's ability to understand and respond to requests
Minimum Qualifications
- Experience in data science, machine learning, and analytics, including statistical data analysis and A/B testing
- Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
- 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)
- 5 years of relevant work experience
- B.S. in Machine Learning, Computer Science, Statistics, Operations Research or related areas
Preferred Qualifications
- Hands-on experience with online AB testing platform
- Experience designing, analyzing and interpreting experiments
- Hands-on experience with on-device logging and metrics development
- Experience with large language models, leveraging LLM for evaluation and product improvement
- Ph.D. in machine learning, computer science, statistics, operations research or related areas
- 8 years of relevant work experience
Equal Opportunity
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0 reports
$121,979
total / year
Base
-
Stock
-
Bonus
-
$103,682
$140,276
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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