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Currently present in over 1000+ towns and cities, food tech giant Zomato is connecting customers, delivery partners, and restaurant partners, serving their multiple needs. The company has delivered close to 2.5 million orders in 2021 and is expected to touch 1.6 billion by 2026.
Today, customers use its platform to search and discover restaurants, write reviews, order food online, book a table and make payments while dining out at restaurants. On the other hand, it offers restaurant partners marketing tools to help them engage and acquire customers to grow their business, alongside providing a reliable and efficient last-mile delivery service. In addition to this, the company provides a one-stop procurement solution called Hyperpure, which supplies high-quality ingredients and kitchen products to restaurant partners.
Cooking data science recipes
On the backdrop, Zomato has been heavily investing in AI/ML, data science and analytics to offer a personalised experience to its customers, driver-partners and restaurants.
Zomato told AIM that it recently worked on a project to ‘strengthen the recommendations that their customers see.’ The team used classical recommendation algorithms to consider customers’ past behaviour and create interaction features. However, at times, this got limited to only the items (say, restaurants and dishes for them) that the customers would interact with, leading to sparsity where customers were found interacting with only select restaurants and/or dishes.
Instead, they used knowledge graphs to predict which restaurants, dishes, and cuisines would go well with their taste. Because a customer can be linked to a ‘never ordered before’ from a restaurant that is also connected to other customers – allowing them to refine their recommendations consistently. Hence, they ran a few experiments with graph algorithms and observed their viability for automating recommendations.
Check out how Zomato used data science to perfect its restaurant recommendations here.
Inside Zomato’s data science team
“Our journey started as a very small team of four members in 2018, and gradually we have grown 5x from that,” said Manav Gupta, head of data science at Zomato.
The company currently has about 20+ members in its data science team and is looking to hire more in the coming months. The team includes ten data scientists, three senior data scientists, three lead data scientists, two principal data scientists, one AVP and one VP data science.
“From identifying the problem statement to finding the solution to deploying and measuring the impact, end-to-end ownership is on us,” said Gupta.
He said being a food tech company, they have multiple stakeholders. This includes customers, restaurant partners, and delivery partners. “We need to ensure all the moving parts work in sync with each other, and this is where the data science team comes into play,” added Gupta.
He said that there are multiple touchpoints during their stakeholders’ journey on the app. “As a team, we ensure that at every point, the experience is seamless using algorithms. We have built models to ensure that while customers see personalised dish/restaurant recommendations, our restaurant partners are also connected to the right customers that help in the growth of their business. Once the customer places an order, our algorithms make sure that these orders are mapped to the closest delivery partners,” said Gupta.
Further, he said they constantly work towards improving the order take rate (OTR) conversions through better customer targeting, search, and recommendation engines. He said their algorithms optimise for the funnel conversations, i.e. the time it takes for a customer to place the order. Amidst all these multiple projects, they also make sure they are maintaining the platform hygiene through their fraud prevention projects.
Interview process
Zomato’s hiring process is quite straightforward. Here’s what you need to know:
- Round 1: Exploratory call. This is to understand if the candidate has the right skills, the right mindset, and the hunger to succeed and create an impact.
- Round 2: Technical Round discussion. This would include an in-depth discussion of the candidates’ past projects, their problem formulation and implementation of DS algorithms. We would primarily evaluate their mathematical understanding behind the algorithms and knowledge of the use cases and pitfalls.
- Round 3: A business case study. Candidates are given a real-life Zomato business problem to exercise their lateral thinking process. This helps them understand how they would solve their current business problems using machine learning and gives a taste of the Zomato life to the candidate.
- Round 4: Hands-on skills (coding assignment). Candidates are given a problem statement, and the data is provided to them to be solved within seven days. Candidates are evaluated based on
- Exploratory data analysis
- Coding structuring
- Model development and evaluation
- Final presentation
“For all of us, fulfilment at work is about more than just the impact we create for the business. The relationships we forge, and the friends we make, are significant contributors to how fulfilled we feel at work. It also adds a lot to how much we feel for the company and, as a result, the impact that we create on our mission. Hence, the candidate being a culture fit is extremely important for us,” shared Gupta.
Do’s and don’ts
Gupta said that candidates tend to focus only on technical jargon and lack an in-depth understanding of algorithms used previously in their work. “We look for candidates who not only have an understanding of data science but who can also think in-depth about how to solve business problems,” he added.
He said they are a solution-first company, with the speed of execution being paramount. “Candidates try to force-fit one class of algorithm to every solution. We don’t want such people. Instead, we want people who understand that every problem is unique and would require a more catered solution,” added Gupta.
Expectations
“Zomato is an organisation where we put our minds and souls every day into pushing ahead. We are a team of people who are striving to make a difference in the food tech industry. We look for people who have the hunger to learn, who are curious and start every question with ‘why?'” said Gupta. He said that they believe that every individual is unique.
Work culture
At Zomato, the DS team functions as a business team – one where they own the problem statement and the outcome. This means the DS team works with the engineering team, product managers and business leaders to ship a feature/development.
“If we had to sum it up in one sentence – ownership is at the core of everything we do here. Our North Star is making our customer experience the best in the world,” said Gupta.
Why join Zomato?
“We have no qualms about putting talented people at the right places, where they can add the most value to Zomato. We endorse an organisational culture that bets on exceptional talent. With being a part of Zomato, you would be exposed to products and technology that are shaping the food tech industry in India,” said Gupta.
Further, he said that the company has a long culture of fluidity. “If you see something that needs to be fixed at Zomato, it’s yours to fix. Being a flat organisation, you get the opportunity to work with business leaders across different verticals directly,” he added. He said that candidates also get a chance to participate in research programmes that they conduct in collaboration with premier academic institutions in India.
“Zomato is a fast-growing company at the forefront of disruption in the food tech industry, and we are only one per cent done,” said Gupta. He said if you are someone who often asks ‘why not?’ and have the hunger to do more, Zomato is the place for you. “We are problem-solvers with a customer-first mindset,” he added.
“While using algorithms as tools to solve the problems is of paramount importance, your pragmatism on how and where to use the tools is what we’re looking for,” concluded Gupta.
What are you waiting for? If you feel you are the right fit, send your CV or resume here.
