Moving beyond frontiers in Data Science – Interview with Mahesh Kumar, Founder & CEO, Tiger Analytics

Kunal Jain 06 Apr, 2017 • 6 min read


This DataFest, we are bringing thought leaders & influencers from industry as part of our interview series – Moving Beyond Frontiers in Data Science section. We are featuring founders of top data science & analytics startups. These leaders have challenged the status quo to redefine the industry.

We have done these exclusive interviews to understand their journey and learn from their perspective.  Here’s the first interview of the month of – Mahesh Kumar, Founder & CEO, Tiger Analytics.

Mahesh has 14 years of experience in predictive analytics, statistical modeling and machine learning with applications in the fields of retail management, digital marketing, e-commerce, customer analytics, transportation, energy planning, and healthcare.

Mahesh was an Assistant Professor at R.H Smith School of Business before starting Tiger Analytics. He holds a PhD in Operation Research from Massachusetts Institute of Technology.

Read on to know about his journey & story of setting up Tiger Analytics.


Kunal: Hi Mahesh, thanks for finding out time for this interview. You started Tiger Analytics after teaching Operation Research at R. H. Smith School of Business. What gap did you discover in analytics industry which persuaded you to start Tiger Analytics?

Mahesh: When I was teaching data analytics, I used to consult for several clients for their analytics needs. In the process, I realized that there were lots of players in BI & Reporting, but very few focused on advanced analytics – especially being able to use data science to address complex business problems. Hence I started Tiger Analytics with an emphasis of creating an organization that uses advanced analytics focused on delivering tangible business outcomes


Kunal: How did you meet your co-founder and the initial team?

Mahesh: I connected with Pradeep Gulipalli, my co-founder, during the early days, while looking for someone with complementary skills and the passion for building a firm truly specializing in advanced analytics. Between us we covered functional expertise, business operations, revenue generation, global delivery etc.

To build the initial team, Pradeep and I primarily used our professional networks to identify personnel with data science and advanced quantitative skills. Today, we are a team of 150+ data scientists and data engineers, solving problems using advanced analytics.

Pradeep Gulipalli & Mahesh Kumar (left to right)


Kunal: What were the challenges you faced during the initial months of Tiger Analytics?

Mahesh: There were several challenges ranging from sales to recruitment to infrastructure. When we started, the only way to convince potential clients to work with us was through our individual resumes. Every sales discussion would be like a business, technical, and data science interview rolled into one. Today, as a company, we have built credibility as a premier data science solutions and services firm.

Similar challenges existed when bringing together a team. To join us, one had to believe in our vision to build the world’s best advanced analytics firm, when we even did not have an office. Today, we have a top-notch data science community and attract top talent.


Kunal: Tell us about your first success story?

Mahesh: One of our initial projects was with a leading North American railroad company. One of their biggest expenses was in replacing damaged wheels. To identify them, they had sensors on the railway tracks, which streamed data when wheels pass over them. The problem was that, at times the sensors would be damaged, because of which they would provide wrong readings, resulting in the replacement of perfectly healthy wheels. This resulted in significant avoidable costs.

We built a warning system that would analyze the sensor data to predict if a sensor was damaged and needed inspection. This project was a huge success and today our algorithms process sensor data from railway tracks all over the US and Canada. There are lots of similar interesting stories featured on our website and I would encourage readers to go through them to get a feel of our work.


Kunal: What differentiates you from your competitors?

Mahesh: Our ability to deliver quality data science and advanced analytics solutions is one of the biggest factors for multiple Fortune 500 companies from a wide range of industries to work with us.

Internally, we have a significant emphasis on culture and work-life balance and strive to ensure that people are happy to work with us. The atmosphere is informal and authentic, and very professional. Additionally, opportunities to solve cutting-edge big data analytics problems keeps our team motivated and excited.

We are building a company that is focused on quality first – in terms of work, customers, and employees – and are not in a haste to scale rapidly, as it could cause the quality of work to suffer. We will scale but in a gradual manner.


Kunal: Did you expect such massive growth & success in a short span of time?

Mahesh: The response so far has been phenomenal. We have worked with 50+ clients in a span of 5 years: many of them are marquee names from the Fortune 500 roster, and almost all of them are repeat customers. Our business has been expanding at a healthy pace.

In 5 short years, we have established a niche for ourselves in the data science space as a dependable partner for organizations across the globe. We have been ranked by Deloitte as among the Top 10 fastest growing tech firms in India in 2016.


Kunal: What are the top priorities as the CEO of Tiger Analytics?

Mahesh: My top 2 priorities would be:

  1. Work with clients to identify areas where advanced analytics can help address business issues – guide them through the new wave of analytics that is sweeping organizations worldwide
  2. Provide a good work environment where our employees feel excited and motivated – help them learn the nuances of analytics and the big picture of business applications – groom the analytics leaders of tomorrow


Kunal: You have a presence in multiple locations – how is the set up in each of these countries?

Mahesh: We started in the San Francisco Bay Area and have our primary delivery center in Chennai, India. Our teams work out of both these offices as well as from customer locations globally.


Kunal: What are the different analytics solutions offered at Tiger Analytics?

Mahesh: We offer custom services and solutions in the areas of Marketing Science, Customer Analytics, Operations & Planning, and Risk Analytics. The services span Data Science, Big Data Engineering, and Business Analytics.

We have developed a portfolio of proprietary process accelerators and solution blueprints that underpin our project execution.


Kunal: The awareness for analytics is increasing among students & professional. Do you think the candidates are well-prepared for the role today?

Mahesh: We find that business analytics courses including platforms such as Analytics Vidhya, do a commendable job in equipping aspirants with the tools required for a career in analytics. However, we see some very frequently occurring gaps – the primary one being of first understanding the business problem and data before beginning a modeling exercise.


Kunal: What are the skill sets you look for in a candidate while hiring? And what is the selection process?

Mahesh: Depending on the role which we hire for, we look for programming, quantitative, and/or business aptitude. For someone starting their career, deep understanding of data science is not expected, but that becomes the expectation for a relatively senior role.

More than the above, culture-fit and coachability of a candidate is very important to us. In a field that is evolving rapidly, one should be able to unlearn and relearn.


Kunal: What impact do you think analytics & big data will have in the next 5 years?

Mahesh: We are seeing a significant increase in the volume, variety & velocity of data, decrease in data storage costs, increase in computing power, and availability of new methods and tools. Most crucially, with an increase in business adoption, the scope of big data analytics has increased manifold.

The emergence of positions such as Chief Analytics Officer and Chief Data Officer indicates how seriously analytics is now being viewed at the highest level. Enterprises are understanding the need to think data-first as it is increasingly playing a critical role in determining business direction.

We anticipate that analytics will see significant growth in the next 5 years.

Kunal: Any advice for students and working professionals?

Mahesh: Analytics is a very attractive career option today. Whether you are a student or a professional, if you are someone who wants to solve problems, work with data, learn new math concepts and technologies, then you should seriously consider analytics as a career option.

There is significant innovation happening in the field and new application areas are emerging. In the future, we will see several professional opportunities that don’t exist today. It’s exciting to be a part of this new wave!


Kunal: Thanks Mahesh for your time and thoughts. I’m sure a lot of people will be inspired by your story and will be motivated to join the analytics industry. 

Check out the activities coming up in AV DataFest 2017

Learn, compete, hack and get hired!

Kunal Jain 06 Apr 2017

Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.

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Responses From Readers


Mohit Kumar
Mohit Kumar 06 Apr, 2017

Thanks Kunal for sharing these interviews, It really gives insights into what goes inside the big data, analytics companies. And how people are leveraging the analytics part to solve real world problems. The point i get from their first success story is that ,"One must not treat data as word of gospel even if it is coming from automated sensors,machines. " . And Secondly, feedback part is very important for improving the model apart from all the fancy algorithms and hyperparameter tuning.

Mantej Singh Dhanjal
Mantej Singh Dhanjal 06 Apr, 2017

Great article!

Raj Salecha
Raj Salecha 06 Apr, 2017

Thanks for sharing the interview..

snehanshu 06 Apr, 2017

good article

hossein 07 Apr, 2017

thanks Dear Mahesh & Kunal I wanna expand my knowledge in retail analytics do you have any practical resource advice?