Thulasi Nambiar

Senior Manager, Marketing Data Science at Prosper

Analytics & Strategy leader with a proven track record of building, scaling and leading teams to deliver business growth and generate revenue. Global experience in strategic analytics, data science, machine learning, artificial intelligence, product and business strategy, operations optimization, sales growth & business analytics. Exceptionally skilled in cross-functional communications, client relations and deal negotiations across fast growing technology startups and global banking organizations. – Speaker at UCLA Finance Industry Night. – Awards: Winner of BlockChain National Hackathon 2015. – Press Mentions: Appeared on CoinDesk for uncovering new application that could improve financial infrastructure and increase global financial inclusion – www.coindesk.com/blockchain-insurance-consensus-2015-makeathon

WATCH LIVE: December 8 @ 3:25PM – 3:55PM ET

Building a data science team from ground up

As most companies understand the power of data and learn of the advances in data science, a common theme appears. The one where companies hire a single data scientist and expect astronomical changes to the technology or growth. What is lacked in most cases is the discipline to understand that like many other things in life, data science is a process – a sprint, and not a marathon. Building a team from ground up takes time and if done efficiently can in the future lead to substantial competitive advantage. I would like to talk about how to do this in a structured and most optimized way.