Senior Data Scientist, IBM
Raksha is a Sr. Data Scientist at IBM GBS focused in cognitive business decision support, aligned to the distribution industry. She has deep experience in retail analytics having worked in the domain of machine learning, supply chain analytics, price optimization, demand forecasting and inventory management with various retail and CPG clients. Prior to IBM, she worked for oracle corporation as a part of their data science division
WATCH LIVE: November 2nd at 11:00 am
Today’s technology suite enables retailers to collect a wealth of information about customers as they make buying decisions. This presents a challenge: how to take full advantage of this information and use it to answer critical business challenges. As a part of the Cognitive Business Decision Support team at IBM, I work closely with clients from the Retail and Consumer Products industries and end users, as well as strategic partners from the IBM Research team, to develop innovative solutions that address retail challenges. The crossdisciplinary work involving working with experts from operations research, machine learning, mathematics, physics, management science. This collaboration in turn helps me as a Data Scientist, to continuously push the boundaries of applied data science techniques in varying business contexts using the latest technology. Over the years, our go-to market solutions have focused two core areas of data science – Descriptive (What happened?) Predictive (What will happen?) These two areas then come together under Cognitive Analytics to answer – What should we do next? In today’s talk, I would like to talk about 2 main business challenges that I had an opportunity to work on recently – 1. For a leading consumer product client, how do we rapidly sense demand shifts during Covid-19? 2. For a home improvement retailer, how do we design an optimal pricing strategy in the face of increasing tariff costs?