Data Scientist - Live Television Streaming Service
San Francisco, CA
Location/City : CA - San Francisco
Area Code : 415
Job Type : 1: Full Time
Id : 23259
#23259 Data Scientist - Live Television Streaming Service
Location: San Francisco, 94107
Our Client is a San Francisco-based startup building the future of television letting you watch your favorite shows on all the devices you care about with intelligent search, insightful discovery, and effortless sharing. Their leadership consists of founding team members from Facebook and Meraki, and brings deep industry experience to the team. They're a small team that puts our product experience first. They foster a flexible work environment that is supportive but allows for autonomy so that everyone on the team can help us build towards our vision. Our client's engineers own what they build from start to finish. They ship to production multiple times per day and keep unnecessary process to a minimum so they can maintain our pace of rapid development. They value pragmatism, having pride in our work, and deep transparency at all levels.
Our client is seeking a Data/Analytics Lead with demonstrated experience in statistical modeling, SQL, and independently developing data driven insights. This data science enthusiast would have the opportunity to leverage massive structured, unstructured, transactional and real-time data sets from a variety of sources, analyze financial and customer usage patterns, and make actionable recommendations using statistics, business understanding and common sense. The resulting insights will be a critical component of decision making around product innovation and marketing spend.
-Collaborate with the engineering team on data structure to support advanced analysis of customer acquisition and retention efforts (influenced by product features and marketing activity).
-Collaborate on KPIs, own and manage regular reports and scorecards around funnel performance and marketing initiatives, some include: LTV measurement and optimizing CAC.
-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.
-Develop customer propensity models, with an emphasis on logistic regression to understand key drivers of high value customer behavior and support. personalization initiatives.
-Maintain standards for tracking and measurement.
-Deliver quick insights on ad hoc projects and analyses as necessary.
-Passionately analytical and innately curious creative thinker
Solid technical database knowledge and experience optimizing SQL queries on large data sets.
-Experience in logistic regression, with preference for experience also applying other modeling techniques and data classification (e.g. cluster, factor, decision trees, etc.).
-Ability to explain and present analytical methodology and results to non-technical audiences.
-Hands-on experience with statistical (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.
-Hands-on experience with BI and visualization tools (e.g. Tableau, Periscope, Domo).
-Programming skills, in particular experience with statistical libraries in python.