“Grab and understand the utility of your hammer and it will help you find all the right nails to fix,” says Rohit Pandharkar, Head of Data, Circles. This is an excerpt of our brief interaction with Rohit and if you are a fresher in the field of Data Science and Analytics, look how interestingly he lays the initial stepping stones for you.

Please tell us about your journey and what a day in your current role looks like.

• I am an engineer in Telecom and Electronics, after that, I completed my master's at the Media Lab at MIT, in Boston. I served as the head of data science at Mahindra Group of Industry, as a global head of data science at OLX autos, and am currently leading the data science department for a multinational telecom SAS company, Circles.
• To summarise professionally I have covered all three aspects of Data which are Data Engineering, Business Intelligence and Data Science. So my profile revolves around creating Data Strategies, ML Models, building credit scoring Engines, Pricing Engines, Recommendation Systems for Hotels etc initially and as a senior now with the advancement of Gen AI etc which has a lot of business Impact I get to talk to many CEOs and company leaders because the demand is beaming in all spheres of industries.

So, while hiring talents in your team what are you looking for in your best candidates?

The main criteria we look at is the portfolio of projects. Having hands-on experience across many projects is always a big plus. Having an understanding of projects like recommendation systems, defaulter prediction, and Pricing engines for cab lending projects because they carry practical importance is a fair expectation from someone with a brief experience.

• The second criterion is understanding the sense of your definitions, you must understand their implications over the projects you have completed. For example, when asked about the difference between Precision and recall, apart from the definition, we must know its calculations and impact on the decisions we make. A self-driven person with a sense of sales, an experimental approach, and the ability to articulate in front of the leadership will be I say, a great addition to a team.

With the technological goalpost changing regularly and new advancements like Gen AI making headlines in the tech world daily, how to keep pace with the innovations?

• You don't have to run and parrot out whatever new is thrown in the market. Pick up some of the most important problems from the industry which are prominent in finance, healthcare, and retail.
• Once you identify the problem, pick up and choose from how and which of the algorithms can solve it, move on to solving and see the results. Continue polishing your results, and check for side factors like oversampling, regularization, overfitting etc as this will enhance your knowledge tree in the process while you are getting a practical experience.
• To make the best use of the concepts come up with multiple algorithms and models to try and solve the same problem.
• For the new innovations, know their utility and experiment whenever practically possible, and move on, as we can master them later in the process.

You know about how SETU is making the candidates learn about real-life business problems from the industry and we are following almost a similar approach of learning while solving, apart from that what suggestion do you have for us?

• That’s a wonderful initiative, as while the candidate solves a real problem from the industry they are motivated throughout and this increases their interest in their domain, which is crucial. Apart from traditional theoretical learning, this is a much more effective way of learning. Let the candidates know to be assured that it's a very rewarding and interesting career because it has both business impact as well as technological involvement where you don’t only exploit your managerial strength but closely utilise your engineering strength as well.
• As a suggestion, I will recommend focussing on collaborative learning and team playing. See how your peers are solving the same hurdle! This gives us the idea that different minds can come together and solve a major problem in a better and more effective way.
• Also, never underestimate the power of disciplined learning. We had our ways of learning, and we were prompt in our days as well. Now you have platforms like SETU’s Codeverse, to pick up the problems and the relevant data sets to get your hands dirty. This discipline will take you long ahead in your learning curve as well as in your career.