An app-based on-demand platform for at-home services, Urban Company, which started its journey in Delhi in 2014, with just a handful of service professionals, has now expanded to a network of over 35,000 hand-picked service professionals, with operations in 35 cities in India, the UAE, Singapore, Australia, and the Kingdom of Saudi Arabia. 

The company, today, offers a gamut of services, including beauty and spa at home, cleaning, plumbing, carpentry, appliance repair, painting, etc., via its mobile app and websites. But the question is how it manages hundreds of thousands of gig-force workers and customers each day to deliver high-quality and seamless services at home for its customers. 

The answer to this led us to its data science team, which is at the core of everything Urban Company does today. The team helps fine-tune different business and product areas like compliance, matchmaking, trust and safety, fraud, credit risk, customer/partner value, etc. 

“These assist in delivering high-quality services to 6 million+ customers while providing great and stable employment opportunities to 35,000+ partners. Also, we help in driving top-line while maintaining bottom-line for the business,” said Sumit Gupta, director and head of data science at Urban Company. 

For example, Urban Company, in the mask classification task, uses identity verification on-job to deliver high-quality and trusted services. Check out the images below, which showcases various findings on how the company uses this technique to ensure the safety of its partners and customers and bring a standard process in place.  

Besides this, Urban Company also uses credit risk to assess partner value and help high-value partners through various kinds of loans. 

Currently, the company is actively hiring data scientists and data analysts across various experience levels in Bengaluru. 

Team Structure 

Urban Company data science team consists of five scientists and growing. The company follows a flat structure, with the data scientists reporting to the head of data science. 

Interview Process 

At Urban Company, the interview process for data scientists consists of four-five rounds depending on the level of hiring. 

Round 1: Data science/machine learning (ML) basics (Maths) 

Round 2: Data science/ML advanced (Application of ML via case study) 

Round 3: Analytical thinking (Analytical thinking via case study) 

Round 4: Product fit (Overall problem-framing, Solutioning) 

Round 5: Bar Raiser 

Expectations

“We are looking for strong problem solvers with good basics of ML and strong intuition with data. Data science is as much an art as it is a technology field where intuition with data and problem-framing play an important role as the know-how of ML techniques. So we evaluate candidates on all these parameters,” said Gupta. 

If you are planning to apply at Urban Company, here are some of the key areas to consider:

• Core ML concepts: In-depth knowledge of ML algorithms and their assumptions (if any)
• Applied ML: How well does a candidate structure a real-life problem into an ML problem, what different solutions are proposed, what are the pros and cons of the proposed solutions?  
• Analytical thinking: How can the candidate take a relatively simple probability/stats problem and solve it?
• Product-fit: 360 views of solving a real-life problem (variable, methodology, problem-framing) 

“A candidate with strong ML concepts, experience in applying ML to real-life problems and feel/intuition for raw data should be able to crack the interviews,” said Gupta. 

Further, he said most real-life problems are quite unstructured and require a lot of data gathering and processing before even getting to the model building (which is probably the easiest link of the whole chain). “Apart from these, deployment experience and good engineering skills are a great plus,” added Gupta.  

Dos and don’ts 

Gupta said that many candidates are not passionate enough about data, and they are not able to structure problems and think of variables. “Mostly, they do not even have core ML concepts, which is extremely important,” he added. 

Work Culture 

Urban Company has a strong set of seven culture values, with ownership being the most prominent across teams. The team believes that these values work as a system to help bring the best balance in their day to day work at Urban Company. In addition, it is known for customer obsession, where it continuously innovates to unlock value. “We strive for win-win by value creation for the ecosystem as a whole,” said Gupta. 

Further, he said, first principles are a value that helps them ensure that they are not doing things for the wrong reasons. “We are bold, and we take big bets and think long term. Also, we are biased for action and index on velocity, i.e., moving in the right direction with speed. Lastly, we like to keep things simple,” said Gupta. 

“Apart from this, the data science team has a good balance of research and application with the focus on creating tangible impact. It works as the supervising principal for our team,” he added. 

On a concluding note, Urban Company is driven by the pursuit of creating impact. It is also a workplace that values fairness and merit—a place for high-achievers, promoting a culture of pushing their boundaries and unlocking their ability. Plus, you can expect performance-linked rewards pay-out, ESOPs for high achievers, and a fast growth trajectory. 

What are you waiting for? Click here to apply for data science jobs at Urban Company.