Data Science Leader, Aiml Data Operations

Apple Apple · Big Tech · Cupertino, CA +1 · Software and Services

This role leads a Data Science team focused on AIML Data Operations, establishing health metrics, identifying growth drivers, and recommending optimizations for high-quality annotated data to support unreleased AI products. The focus is on analytics, experimentation, and building cross-functional relationships to drive data-informed decisions.

What you'd actually do

  1. Establish a center of excellence for Data Operations Data Science team by uncovering business-actionable insights in collaboration across our customer groups as well as the Operations team.
  2. Oversee large complex projects from conception to completion, develop roadmaps and requirements, identify risks and develop contingency plans, evaluate impact, and regularly communicate status to executives.
  3. Establish, enhance, and socialize key operational metrics that accurately represent the business state of health.
  4. Lead proactive analyses identifying key drivers of metrics, and make recommendations that optimize performance.
  5. Develop reporting measures to expand the portfolio of self-service dashboards and reports to inform, enable, and empower relevant stakeholders.

Skills

Required

  • SQL-based languages
  • large-scale data languages
  • Python
  • R
  • data science
  • analytics
  • data operations
  • schema designs
  • relational database
  • big data technologies
  • ETL
  • code management
  • query performance optimization
  • interpretable machine learning models

Nice to have

  • deployment of Large Language Models / Generative AI in service of efficiency in operations
  • AI & ML annotations and collections areas

What the JD emphasized

  • 4+ years of experience in managing data science, analytics, or data operations teams
  • 4+ years of experience in data science with proven skills in developing meaningful and concise analytic objectives from general business goals
  • Tested capabilities and comfort in scalable schema designs, relational database and big data technologies, ETL, code management, and query performance optimization
  • Strong hands-on experience interpretable with machine learning models and sophisticated analytic solutions using scripting tools such as Python or R

Other signals

  • delivering high-quality annotated data
  • AIML Data Operations Annotations Analytics team
  • establish top-line health metrics
  • recommend operational and business optimizations
  • leading teams to surface and communicate key data insights