Optimising organized transport at scale - A quick introduction to Data sciences @ Olacabs
Submitted by Swaminathan Padmanabhan (@swaminathankp) on Thursday, 1 October 2015
Section: Sponsored session Technical level: Beginner
The objective of the talk is to introduce the audience to some of the problems that the Data sciences group @Ola works on.
The objective of the talk is to introduce the audience to some of the problems that the Data sciences group @Ola works on. Ola being the largest organized taxi aggregator in the country, the Data sciences group @Ola is entrusted with a wide range of problems such as pricing, navigation/ETA prediction, demand forecasting and the like. Time permitting, we will also provide some highlights on the data infrastructure, learning algorithms and tech stacks that we use.
Swaminathan is currently the principal data scientist, and runs the Data sciences group at Olacabs. Prior to that, he was in the advertising technology space with Inmobi and Yahoo. He has also been involved with startups in advertising, e-commerce, healthcare domains. His focus is primarily on getting machine learning algorithms to work on big data at scale and be useful to businesses. He has worked on areas including real-time prediction/decisioning systems (CTR prediction, ETA estimation, etc.), marketplace optimisation (arbitrage, budget allocation, pricing, etc.), user behavior modeling (ad fatigue, conversion funnels, etc.) and the like.