Machine Learning Engineer - People Analytics

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