Why is Swiggy focusing on data science and machine learning?

If you have come across the recent hiring at Swiggy, you may have noticed positions for data scientists making a frequent appearance at all leading portals, ardently looking for data enthusiast who can play with data and build data-driven products. As this online food ordering and delivery platform is on a serious mission to double its technology team, Swiggy has made its intentions clear on investing in technologies like data science and machine learning for its business benefits. As the technologies like artificial intelligence and data science have diffused into almost all the leading industries—including fashion, Swiggy is no exception. Also, at a time when leading food tech startups have met unfortunate fates of being shut off or being downsized, despite a promising start, it becomes necessary to keep up with the pace of technological needs and have the right thing at the right time. Standing with the same, Swiggy recently took a strong stand of using the $80 million raised in a Series E funding round led by South African media and internet conglomerate Naspers Ltd., to build its capabilities stronger in engineering, automation, data sciences, machine learning and personalization. With a focus on SLA predictions, building recommender systems, personalization, fraud modelling, inventory stock predictions and more, they are keen on experimenting with different areas of machine learning, statistics, fetching data and creating prototype modelling for solving various problems that they currently have issues dealing with.

What makes Swiggy have an upper hand compared to others?

In an era, where there is a herd of online services, food ordering platforms is no exception. Amidst various ideas floating the market, Swiggy has made it a point to stand apart from others. Right from having its own technology platform to its own delivery fleet consisting of smartphone equipped personnel, guided by an app powered by routine algorithms, the company has made sure that it picks up order from restaurants and deliver to the customers without any hassles. Standing up the competition from the likes of Foodpanda and Zomato, Swiggy currently is a team of close to 1200 people across eight cities of Bengaluru, Gurgaon, Delhi, Hyderabad, Kolkata, Mumbai, Pune and Chennai. After four rounds of funding from the likes of Accel India, SAIF Partners India, Bessemer Venture Partners, Harmony Partners and Norwest Venture Partners, and a tie-up with close to 5000 restaurants, Swiggy intends to stay here, amidst fierce competition. They have earlier come with interesting ideas such as building cloud kitchen or a scalable platform that can support lakhs of orders per day. Cloud kitchens are a concept where existing restaurant brands can prepare food solely meant for delivery, thus reaching out to customers even if they don't have a physical presence.

Why go for data science and machine learning?

With the large funding that they have received, this food tech startup plans to hire engineering talent and develop deeper technology for reasons such as—making a better prediction of demand, sort out the consumer preferences in a better way, improve their delivery efficiencies and look into suitable geographical locations to expand its centers. As mentioned, they boast a fully scaled technology platform but they are keen on growing their data science and machine learning capabilities to reap further benefits. With an aim to double its engineering team, Swiggy is looking to hire middle and senior leaderships in the team. It is no doubt that being “data savvy” is the new requirement for industries and working with unique data is something that every organization is adopting, to make sense of it. In such a scenario, Swiggy believes that building end-to-end true data products—right from conceptualizing the mathematical problem to building relevant data models and ML models is the need of the hour. A full stack data scientist is what Swiggy is currently looking for and we can’t agree more on why! Apart from extending its technological reach, the company also plans to utilize a part of its capital to increase the service offerings of Swiggy to restaurants as well. As the company is transforming the way India is utilizing online services to order food, it becomes crucial to understand the customer needs, identify the dents, reach those gaps in the market and offer what it has been missing on. Swiggy has already made a mark with its exceptional user experience, curation of merchants, its own delivery fleet, centralized kitchens, and strong understanding of logistics policies with Swiggy Assured, and with ML and data science, it wants to further improve upon aspects such as customer engaging and deliveries. After a turbulent journey, where it had incurred losses of Rs 137.18 crore during 2016 and with a business model with very low margins, it is extremely essential for the company to keep withstanding the losses and make their business more sustainable—which deep learning and data science ultimately aims to provide.

Why is Swiggy keen on strengthening its data science and machine learning capabilities?

Why is Swiggy keen on strengthening its data science and machine learning capabilities?

What makes Swiggy have an upper hand compared to others?

Why go for data science and machine learning?

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