Sarah Aerni

Member Board Of Directors at Women in Machine Learning

Technology leader with experience in Machine Learning for over 15 years. 7 years in management, currently an organization of 30 data scientists and engineers that deliver and manage models in production. Strengths in delivery to production, collaboration with teams (like platform engineering), and partnering with product managers to shape AI product. Team-oriented, customer-obsessed, quality-focused with an eye toward bringing agile and engineering excellence to machine learning. I motivate teams by working shoulder-to-shoulder with them to help understand their challenges, help unblock them, and coach them toward independence. My top priority is to drive teams to realize their full potential. Salesforce experience leading hybrid engineering and data science teams shipping products producing billions of predictions daily across thousands of models using a fully automated machine learning pipeline. Salesforce Products: Einstein Prediction Builder Einstein Recommendation Builder Einstein Case Classification (Service Cloud) Predictive Lead Scoring (Sales Cloud) Einstein Engagement Scoring (Marketing Cloud) Led data science teams at Pivotal to build models, strategies and customer teams for dozens of companies (including many fortune 100 companies). Industries include Healthcare & Life Sciences, Financial Services, Government Entities Ph.D. in Biomedical Informatics at Stanford University. I was advised by Serafim Batzoglou (Associate Prof. Computer Science) and co-advised by Stuart Kim (Prof. Genetics). My research interests are in analysis of diverse data, identifying signal from noise in images, sequence and gene expression. I am interested in building teams delivering machine learning products, adapting agile methodologies to the practice of data science. I enjoy working in diverse teams, learning new skills, solving challenging problems, being exposed to new ideas and meeting new people.