In this backdrop, the number of foodtech players and aggregators have swelled –Swiggy, FoodPanda, InnerChef and FreshMenu. The growth is expected because of the increasing internet penetration and proliferation of smartphone users coupled with budding e-commerce market and rising young working population. Staving Off Competition In The Foodtech Market With Machine Learningĭeepmind Launches SOTA Video Generation Framework, ‘Transframer’Īccording to a report by TechSci Research, the foodtech market in India is projected to grow at a robust pace, at a CAGR of over 12% during 2016 – 2021. For example, if we solely look at tree-based models, basic CART got replaced by RF which got replaced by GBMs which is now being replaced by ensemble models – all this in last three years,” he said. “The rest 10% is dedicated to learning and developing – data science domain is evolving very fast, and it is crucial to stay abreast of recent developments. Another 20% of Mehta’s time goes in meeting stakeholders from other teams – since the work directly impacts different business verticals and product features, so alignment with business heads and product managers is critical. Another 30% of the time is spent in meetings with team members – clearing roadblocks, ensuring alignment between data scientists/statisticians and ML engineers/developers who are putting models in production,” he shared. “At an individual level, I continue to be fairly hands-on working directly with data which takes 40% part of my time. Presently, the 150-strong engineering team at Zomato includes data scientists, product managers and analysts. Sign up Driving a data-driven culture at Zomato “It was at DH that I built my first proper classification model and felt the power of data while working on extremely rich user-item level shopping carts - seeing the strong correlations between credit card fraud and the brand of wine one purchased felt magical, rather empowering! Data only got bigger and faster as I moved into the world of click-stream data, but the basics of data modelling and generating critical insights from terabytes of raw data are still the same,” he revealed. He spent close to 5 years at Dunnhumby across Delhi, London and Edinburgh offices and it is there his role evolved from a statistician to a client facing research analyst and further as a client servicing consultant. Naresh Mehta, AVP – Data Science & Analytics, Zomatoįor those in the know, Mehta, an IIT-Madras alumnus started his analytics journey as a consultant with ZS Associate. The team also boasts of a few deep learning professionals who are involved in menu image parsing and UGC moderation for image classification, aesthetic scoring and also do NLP on reviews.
“We are increasingly getting involved in driving commercial and operational efficiencies such, as for logistics optimisation, call centre/driver fleet capacity planning, delivery time prediction, ad delivery, supply prioritization which are some of the key areas,” said Mehta. Talking about his role, Mehta shared the team works on most of the product back-end algorithms such as listing sort algorithm, homepage customisation, user personalisation, keyword search, product feature A/B experiments and clickstream funnel among other areas. Analytics India Magazine caught up with Naresh Mehta, AVP, Data Science & Analytics who leads the data science and machine learning team at Zomato.
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