Lead Data Scientist

Lead Data Scientist San Francisco The Role We are seeking a Data Science Lead with demonstrated experience in leading data-driven product development and comprehensive business analytics. In addition to designing and conducting product experiments, this data scientist will leverage massive structured, unstructured, transactional and real-time data sets from a variety of sources, analyze product usage patterns, and make actionable recommendations using statistical modeling, business understanding and common sense. The resulting insights are a critical component of our decision making around product innovation and marketing spend. The ideal candidate will have competence with statistical modeling and independently developing data driven insights in the face of ambiguity. Experience using Machine Learning to build data-driven product features is a strong bonus. Responsibilities: Collaborate with the product and engineering teams to design, execute and analyze experiments to improve the product, user experience, and signup conversion rates. Collaborate with the engineering team on data pipeline to support advanced analysis of customer acquisition and retention efforts (influenced by product features and marketing activity). Collaborate with groups company-wide (e.g. business development, advertising operations, marketing, and support) on KPIs, including LTV measurement and optimizing CAC. Create and own predictive models for key business and customer performance metrics. Design, build, and maintain automated dashboards that connect data from internal and external data sources to support reporting, data discovery and statistical analysis that inform product priorities and marketing decisions Maintain standards for tracking and measurement Deliver quick insights on ad hoc projects and analyses as necessary Key Qualifications: Passionately analytical and innately curious creative thinker Solid technical database knowledge and experience optimizing SQL queries on large data sets Experience with A/B testing and analysis Experience with advanced statistical methods Excellent presentation and communication skills, particularly the ability to explain and present analytical methodology and results to non-technical audiences Hands-on experience with statistical tools (e.g. SAS, R, Python) 3-5+ years experience in business and data analytics after graduation BS or MS degree in Statistics, Math, Data Science, CS or related discipline Nice-to-have: Hands-on experience with BI and visualization tools (e.g. Tableau, Periscope, Domo) Programming skills, in particular experience with statistical libraries in python Machine Learning and Deep Learning experience 1872 Consulting