Rapido to hire Data Scientists at a package of 18-60 LPA, know about their complete interview process!

Apparently, the industrial market of bike taxi services worth USD 150 million is projected to expand at 20% MoM. Close to 300 million Indians venture out of their homes every day to commute to and fro their workplace or travel to other places. Only about 20 percent of this number of Indians own their own vehicles, and just a percent of bookings happen via taxi service booking apps. 

As per an analytical report by PGA labs,  it is assessed that two-wheeler taxis in India have the potential to create more than 5 million job positions in India, thus giving rise to total revenue of about USD 10 billion. 

Transforming the entire scenario of intra-city travel, Rapido has become India's largest bike taxi service provider. The company's array of services has made last-mile availability affordable for everyone in the country. With more than 25 million application downloads and functional in more than a hundred urban communities across India, it as of now serves near more than a million driver accomplices and a community of more than ten million customer base.

All about the Data Science team at Rapido

At present, the entire Data Science Team at Rapido is a build-up of nearly 35 individuals across various roles, such as data scientists, data analysts, data engineers, and product managers with experience in data-driven product assembling led by progressive experimentation strategies.

"Each one of our product pods is objective, arranged, cross-functional, and require all profiles-data scientists, data engineers, analysts, and item supervisors to accomplish the objective we harbor as a two-wheeler taxi service organization," said Pramod N, VP of Data Science and engineering at Rapido.

Coming to the present hiring scenario at Rapido, it's aiming to build a second era of data-led products and administration, wagering on five basic development regions with better optimization, high improvement, and algorithmic potential, namely:

• The retention of customer-base
• Satisfaction and coordination 
• Focus on quality
• The placement and retention of driver-partners
• Captain's overall earnings

Rapido's hiring-related FAQs

Q. What are the in-demand Data Science roles?

A. Rapido is looking out for potential candidates across the following profiles:

• Data Scientist
• Senior Data Scientist
• Lead/Principal Data Scientist
• Senior Data Engineer
• Senior Data Analyst
• Principal Data Engineer

Q. How many positions are available?

A. 10 positions are open for the candidates to apply, location is Bengaluru as the organization is planning to expand its Data Science team base over there.

Q. What is the salary bracket?

A. The average CTC would range between INR 18 to 60 LPA, depending upon the role and experience levels.

Q. What are the skills required?

A. The candidate,

• Should be versed with various nuances of business and management and should be able to solve business problems by leveraging data.
• Should have the ability to clearly elucidate complex Machine Learning or Deep Learning models.
• Should be well familiar with employing supervised and unsupervised machine learning, statistical analysis, and related predictive modeling techniques.
• Should have proficiency with matrices, statistics, probability, relational databases, and NoSQL.

Q. What is the interview process?

A. The screening and interview for Data Science related job posts will consist of three basic rounds:

• Checking the candidate's hands-on-ability and skills through a given assignment: To comprehend the applicant's capacity for insightful narration by utilizing high-level programming languages, preferably Python and the Scikit ecosystem, or Spark for comparatively bigger scale problems. 
• Technical Round I: Size up the up-and-comer's experience and expertise in science and maths. 
• Technical Round II: Solving a given task or problem within a specified timeframe. The ability to follow best practices while executing EDA, story-telling, model forecasting and development, and related skills would be analyzed.

"During interviews, we clarify the issues we are attempting to address. We don't exactly expect the right answer. Maybe, we attempt to comprehend the competitor's manner of thinking. We additionally need our representatives to numerically legitimize the decision they make while tackling a problem," emphasizes Pramod N.  

"My lone guidance for future applicants would be to be curious and interested in picking up new concepts, and recount a number story," he further added. 

Q. What's the work culture and environment at Rapido like?

A. Well, the team at Rapido believes in making rapid but consistent progress and strives for goal-oriented advancement through a scope of trials. In contrast to most organizations, they can try out theories in a fast, feasible, and iterative style. 

Rapido accepts its 'three in a case model for making Data Science work for business' is quite peculiar and extraordinary to its teams. Their methodologies to solve problems in data science resembles a Tunnel Boring Machine (TBM) having three basic angles, that is:

• The navigation: To decide when to run new analyses and when to take an alternate way.
• The boring apparatus: It addresses Data Scientists and Analysts with sharp numerical abilities.
• The conveyor framework to hold the channel stable: To guarantee that the team is obtaining the right business learnings through its experimentation, and is able to feed into the navigation part for any future analysis.

Rapido hopes to empower and support experimentation drive, functional science, hands-on-ability, practical environment, with endless freedom and numerous opportunities to build various optimizations.

Things to keep in mind

"Quite possibly the most widely recognized missteps made by applicants has been hopping straight into some abstruse Machine Learning or Deep Learning strategy with no reasoning or thinking regarding why," said Pramod N. 

There is not a viable alternative for being curious, inclined, and having scientific thoroughness. "Any individual who needs to work with us should zero in on the core mathematics, numerical abilities and foster a capacity to learn through performing experiments. It's alright not to know a couple of algorithms, you will gain proficiency with the current ones en route, and now and again, you will write a new one when and where required," he added. 

Note: A certain degree of experience of working in a big data environment alongside data engineering teams, data visualization teams, data and business analysts is mandatorily required across all levels.

To check out and apply for various Data Science-related job roles at Rapido, click here.

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