Quantzig is a global analytics and advisory firm that provides end to end data modeling capabilities to leverage analytics for prudent decision making for the clients. The firm consists of 550+ data scientists and analysts, who have served 120+ clients, including 55 Fortune 500 companies that helped them achieve continuous market excellence.

Lalith Velamuri is an analytics professional with 5+ yrs of experience. Currently he is working as a Lead-Data Scientist in Quantzig. His work revolves around delivery of all projects, pitching analytical solutions to clients, help them use their data assets to solve business problems. He landed up in the field of analytics because he has good analytical aptitude from the beginning and always had a taste for mathematics and statistics.

  1. What are the common challenges faced while hiring freshers?
    There is a huge demand in the field of analytics but there is not enough supply of good quality candidates. There is a lack of business knowledge; candidates are not ready for critical business thinking activities which is the bread and butter for any data scientist. There is a hype of Machine Learning, Artificial Intelligence but, analytics is not only about this. Problem solving skills is the biggest gap and how to use this skills are not clear to the candidates. Curiosity to solve problems is the inherent gap.
  2. How do you overcome these challenges?
    We offer on the floor live training to the new joiners where they get trained on real world problems and given projects to work upon to get proper business knowledge. They are given 4-5 months of probation period to prove themselves and do their best. The candidates are challenged with increasing level of problem complexity
  3. What is the skill sets required for a data scientist?
    The pre requisites are the tools and technologies like R, Python, SQL, Excel, BI tools, Tableau. But these don’t let anyone stand out from the crowd. The most important is that they should have consulting skills. They should have good business knowledge, should understand business problems and clients prospective. The business problem solving skills can be acquired by doing various mock workshops or projects.
  4. Do you hire entry level talent as Data Scientist?
    Currently we are not hiring freshers as our standards are very high. So we look for people who can start working from the first day.
  5. Do you think non engineers can perform well in analytics?
    Yes definitely. I believe academic background is not an eliminator to become a data scientist. Engineers do well because of their programming mindset and logical thinking. Being ambitious and competitive is another quality the industry needs. Non-engineers with such mind state can easily get through the interviews
  6. Can you share about an interesting project of your company?
    There are many such, but one which I recently worked on is : We helped clients who are into manufacturing of medical devices like MRI, X-RAY. We helped them understand the perspective of investors, patients, competitors and other information seekers about their products by Webcrawling the publicly available articles, blogs, reviews, research thesis etc. and applying NLP based text mining techniques on top of it to extract the key pain points , topics of interest and sentiments around them. We have statistically quantified the results and integrated them into a web-based tool which captures these data points regularly, runs the machine learning models and visualize the key insights