AIML - Data Scientist, Data and ML Innovation

$135,400 - $250,600/Yr

Apple - Seattle, WA

Full-time - Mid Level

Seattle, WA

Computer and Electronic Product Manufacturing

About the position

The AIML Data organization at Apple is focused on enhancing products through data-driven insights, particularly within the Search Analytics team. This role involves improving the quality of Siri's user-facing products by developing evaluation methods, collaborating with engineering teams, and analyzing user experience data to inform product evolution. The position requires a blend of data science, machine learning, and analytical skills to drive impactful product changes across various Apple devices.

Responsibilities

• Research and develop evaluation methods to improve the quality of Siri's user-facing products.
• Collaborate with evaluation/experimentation engineering teams to implement methodological developments into technologies used by Siri engineering.
• Work with large, complex data sets to solve difficult, non-routine analysis problems using advanced analytical methods.
• Conduct comprehensive analysis including data gathering, requirements specification, processing, and ongoing work.
• Build and prototype analysis pipelines iteratively to provide insights at scale.
• Develop a deep understanding of Siri Search data structures and metrics, advocating for necessary changes for product development.
• Partner closely with Siri search engineering teams on core machine learning algorithms and systems.

Requirements

• Experience in data science, machine learning, and analytics, including statistical data analysis and A/B testing.
• Ability to articulate and translate business questions into statistical techniques for data analysis.
• Strong programming skills, including data-querying skills (SQL and/or Spark) and experience with a scripting language (e.g., Python, R, or Scala).
• Excellent collaboration skills to work effectively with diverse cross-functional teams.
• B.S. in Machine Learning, Computer Science, Statistics, Operations Research, or other quantitative fields.

Nice-to-haves

• Good understanding of large language models (LLMs), including architecture, training methods, and prompt engineering.
• Hands-on experience applying LLMs to solve technical problems, optimizing model performance for accuracy and efficiency.
• Ph.D. in machine learning, computer science, statistics, operations research, or other quantitative fields.
• 5 years of relevant work experience.

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments
• Relocation assistance