Senior Data Scientist, People Analytics

The Senior People Data Scientist will join our People Analytics team within Employee Experience, and report to the Director of People Data Science. This role will work with a team of analysts, data scientists, and data engineers to derive insights and recommendations that inform strategic people-related decisions. 

Responsibilities: 

• Conduct ad-hoc analytical deep dives on complex data, and articulate the takeaways to (non-analytical) stakeholders in a way that drives impact and decision making  

• Explore, prototype and iterate on insights from internal data and research, and determine what and how to scale  

• Develop predictive models to forecast outcomes and inform people decisions. 

• Develop algorithms to auto-extract insights from various data sources 

• Automate compelling, frequent analyses (e.g., via R or Python scripts) 

• Demonstrate deep care for the ethical implications of working with employee data and ensure team compliance with privacy and legal regulations. 

• Define critical data elements, logic and implementation of key people metrics, and our approach to incorporating new data signals 

• Contribute to ensuring we have a solid foundation for managing, processing, and analyzing data efficiently and securely (in collaboration with other technical teams across Adobe).  

Skills/Qualifications: 

• 9+ years of experience applying statistical and machine learning techniques to people data (e.g., survey data, HRIS data, human behavior or product interaction data) in an applied setting  

• Expert knowledge of advanced statistical methods (e.g., regression, cluster analysis, HLM, social network analysis, text analysis, forecasting/predictive models, ML, etc.) 

• Advanced in data querying, hypothesis testing and analysis using tools such as SQL, Python, and R 

• Strong understanding of data infrastructure needs for People Analytics, and ability to collaborate across functions to solidify data foundations  

• Excellent verbal and written communication skills, with the ability to convey complex data insights to non-technical stakeholders. 

• Demonstrated ability to work collaboratively across functions and levels within an organization. 

• Proven ability to mentor junior data scientists and teach others how to use data science tools and best practices. 

• Strong analytical and problem-solving skills.