Sr Data Scientist, Evaluation

Apple; Seattle (WA); On-site; USD 175,000 - 309,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Discounted Apple products and services

Educational expense reimbursement

Relocation assistance

Apple stock purchase plan

Job summary

Apple is seeking a senior evaluation scientist to design rigorous methods for measuring and improving how products learn, search, and respond. You will work on-site in Seattle, WA, collaborating with multi-disciplinary teams to translate analytics into actionable product improvements for Siri and Apple Intelligence.

You will handle large datasets, apply advanced analytics, and explore prompt engineering and LLM-based judgments to drive quality and user experience.

Qualifications

• 5 years of relevant work experience.
• Advanced degree in a quantitative field such as Statistics, Operational Research, Bioinformatics, Economics, Psychology, Computer Science, Sociology, Mathematics, Physics, or similar.
• Proficiency in data science, machine learning, and analytics, including statistical data analysis.
• Experience crafting, conducting, analyzing, and interpreting experiments and investigations, with focus on data quality, evaluation, and risk assessment.
• Strong programming skills, including data querying with SQL and/or Spark and experience with a scripting language for data processing and development such as Python, R, or Scala.
• Ability to translate business questions into statistical approaches and arrive at answers using available data.
• Strong communication skills, with the ability to explain difficult technical topics (including causal topics) to data scientists, engineers, and business partners.

Responsibilities

• Research and develop evaluation methods to improve the quality of user-facing Apple products (for example, Siri and Apple Intelligence).
• Partner with evaluation and experimentation engineering teams to translate methodological advances into technologies that product engineering applies daily.
• Work with large, complex data sets and tackle difficult, non-routine analysis problems using advanced analytical methods.
• Apply techniques including prompt engineering and building LLMs as judges.
• Run analysis that covers data collection and quality control, requirements specification, processing, and presentations.
• Build and prototype analysis pipelines iteratively to deliver insights at scale.
• Develop deep understanding of product data structures and metrics, and advocate for changes needed to support product development.
• Collaborate closely with product engineering teams on core machine learning algorithms and user experience evaluations.
• Stay focused on creating outcomes through a passion for building outstanding products.

Skills

Data science

Machine learning

Analytics

Experiments

Programming

SQL

Spark

Python

R

Scala

Communication

Translating business questions to math

Education

Advanced degree in a quantitative field

Tools

SQL

Spark

Python

R

Scala

LLMs

Job description

Build rigorous evaluation that improves how Apple products learn, search, and respond. In this role on-site in Seattle, WA, you will develop measurement and evaluation methods, collaborate with evaluation and experimentation engineering teams, and help product engineering turn those methods into tools used to improve search quality and feature development across Apple products, including Siri and Apple Intelligence. You will focus on rigorous use of data, including advanced analytics and LLM evaluation.

Salary: USD 175,000 - 308,500 per year. Minimum experience: 5 years. Education: an advanced degree in a quantitative field.

What you’ll do

• Research and develop evaluation methods to improve the quality of user-facing Apple products (for example, Siri and Apple Intelligence).
• Partner with evaluation and experimentation engineering teams to translate methodological advances into technologies that product engineering applies daily.
• Work with large, complex data sets and tackle difficult, non-routine analysis problems using advanced analytical methods.
• Apply techniques including prompt engineering and building LLMs as judges.
• Run analysis that covers data collection and quality control, requirements specification, processing, and presentations.
• Build and prototype analysis pipelines iteratively to deliver insights at scale.
• Develop deep understanding of product data structures and metrics, and advocate for changes needed to support product development.
• Collaborate closely with product engineering teams on core machine learning algorithms and user experience evaluations.
• Stay focused on creating outcomes through a passion for building outstanding products.

Requirements

• 5 years of relevant work experience.
• An advanced degree in a quantitative field such as Statistics, Operational Research, Bioinformatics, Economics, Psychology, Computer Science, Sociology, Mathematics, Physics, or similar.
• Proficiency in data science, machine learning, and analytics, including statistical data analysis.
• Experience crafting, conducting, analyzing, and interpreting experiments and investigations, with focus on data quality, evaluation, and risk assessment.
• Strong programming skills, including data querying with SQL and/or Spark and experience with a scripting language for data processing and development such as Python, R, or Scala.
• Ability to translate business questions into statistical approaches and arrive at answers using available data.
• Strong communication skills, with the ability to explain difficult technical topics (including causal topics) to data scientists, engineers, and business partners.

Preferred qualifications

• Proven ability to collaborate effectively across functions and work well within a team.
• Experience driving projects across different timelines and scopes, including knowing when to dive deep.
• Experience with methods addressing accuracy and variability in human annotation data.
• Ability to learn new technologies and skills to adapt to changing requirements.

Tools you may use

• SQL, Spark, Python, R, Scala, LLMs

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition, to advance your career
• Discretionary bonuses or commission payments and relocation (if eligible)
• Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
• Eligibility for discretionary restricted stock unit awards
• Option to purchase Apple stock at a discount through the Employee Stock Purchase Plan