Senior Machine Learning Engineer - Product Analytics

A successful candidate will have deep experience in applied methods (predictive modeling, classification, product feature impact measurement), experience building reporting dashboards, and using those methods and tools to drive key business insights. The role requires both a broad knowledge of existing data mining algorithms, strong business sense, and creativity to invent and customize when necessary. You’ll work closely with a broad range of data professionals as well as business leaders. You’ll be working on projects where tools and methods are used to drive real-world business value. Successful analytics teams involve data scientists and data engineers working hand in hand to build insightful and efficient solutions. In your role, you will be a key player in a multi-functional team that delivers insights that have direct and measurable impact. We're looking for an inquisitive, collaborative, and passionate person to join this amazing team. - Support Product, Marketing, Partner Development, and the Executive Team with analytics for product performance and customer insight. - Work closely with the product team to identify and size new opportunities, develop data requirements, establish appropriate KPIs, and establish proper reporting. - Become an expert on both the business and the data to drive new insights. - Quantify the impact of product, sales, and marketing initiatives on customer satisfaction, and future behavior. - Manage business analytic projects through all phases, including data quality, data modeling, algorithm/KPI development, statistical analysis, data visualization, and presentation of results and deliverables. - Design and evaluate experiments that help define opportunities for increased usage, improved marketplace performance, and greater customer satisfaction. - Monitor usage metrics, understanding business-based explanations for large scale trends, and patterns in customer lifecycle behavior. - Develop reusable models and assets working closely with Data Technology team to ensure scalability and industrialization as models move into production