Machine Learning Engineer - People Analytics

About the Role

At Apple, the People Analytics Team is dedicated to ensuring Apple's employees are able to do the best work of their lives. We are looking for a Machine Learning Engineer who is passionate about crafting, implementing, and operating analytical and machine learning solutions that have direct and measurable impact to Apple and its employees.

As a Machine Learning Engineer on Apple's People Analytics Team, you will employ predictive modeling, statistical analysis, and advanced analytical techniques to support solutions for talent management, employee surveys, compensation, and recruiting. Apple's dedication to privacy, the human-centric nature of our work, and the scale of our business present exciting challenges to traditional machine learning and data science methods. On this team, you will push the limits of existing approaches while delivering tangible business value.

Responsibilities

• Engage with business partners to understand their problems, design data-driven solutions, and produce proof-of-concept and prototype solutions
• Collaborate with data engineers and system architects to implement solutions in a production environment
• Be responsible for the ongoing analytic operation of these solutions

Minimum Qualifications

• MS with 5+ years of professional experience applying data science to real-world business problems
• Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection
• Proficiency in writing SQL queries involving database joins and analytical/window functions
• Ability to implement data science pipelines, analyses, and applications in a programming language such as Python or R
• Prior experience working with employee data or HR systems
• Ability to translate business processes and data into an analytic solution
• Ability to comprehend and debug complex systems integrations spanning multiple toolchains and teams
• Ability to extract meaningful business insights from data and identify the stories behind the patterns
• Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
• Creativity to engineer novel features and signals, and to push beyond current tools and approaches

Plus: Experience with natural language processing (sentiment, topic identification, summarization, entity extraction) and network analysis

Preferred Qualifications

• Ph.D. in I-O Psychology, Economics, Operations Research, Computer Science, or Statistics with a data science fellowship or prior professional experience as a data scientist
• Experience working with employee data or HR systems