At Apple, our greatest resource is our people, and the People Analytics Team is dedicated to ensuring Apple’s employees are able to do the best work of their lives.
Our team is 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.
Description
As a Machine Learning Engineer on our team will engage with our business partners to understand their problems, design data-driven solutions, and produce proof-of-concept and prototype solutions. They will collaborate with data engineers and system architects to implement these solutions in a production environment, and be responsible for the ongoing analytic operation of these solution.
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
Experience with natural language processing (sentiment, topic identification, summarization, entity extraction) and network analysis a plus.
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
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
