To understand what it takes to become a data science professional, we are reaching out to experienced data scientists every week from the industry. For this week\u2019s \u201cMy Journey In Data Science\u201d we talked to Mathangi Sri, Head of Data Science at PhonePe.\n\n\n\nMathangi has a strong track record of building world-class data science solutions and teams. Before PhonePe, she has worked with some of the top organisations and startups. She has also published more than 20 global patents in data sciences with 10 global patent grants.\n\n\n\nHow Data Science Happened\n\n\n\nMathangi\u2019s journey in data science is undoubtedly one of the most interesting ones. As a child, she was very interested in poetry and literature, and she even dreamt of becoming an author. However, with time, she also developed a flair for mathematics and statistics. When asked about how this culminated into engineering, Mathangi said tartly, \u201cPeer pressure\u201d.\n\n\n\nBy the end of her engineering degree, Mathangi started to feel a strong passion for management, and she ended up doing an MBA from NIT Trichy. When asked about the driving force that got her into data science, she said that once GE (currently Genpact) had come to their campus, and they talked about how they want to choose the locations for windmills based on data. This caught her attention and what she started wondering how they could do that with the power of data. And this is when she fell in love with analytics 15 years ago.\n\n\n\nThe First Job Story\n\n\n\nMathangi was one of the early entrants when the analytics market was picking up in India. She started her analytics career, that is, her first job, with GE (currently Genpact). She added that she didn\u2019t have to struggle too much to land that job. However, she had to wait for the right opportunity.\n\n\n\nDuring her initial days of career at Genpact, she used to create lots of dashboards and reports. She used to use SAS for crunching millions of data. \u201cThis experience anchored me to be very disciplined about numbers. We used to analyse the drop in risk rates in a few basis points. This gave me the training to look for minor variations in data and get very rigorous about it,\u201d said Mathangi.\n\n\n\nWhen asked about her first interview experience, Mathangi said she had a telephonic interview \u2014 the questions were around statistics fundamentals and on logic. Further, they also assessed her communication skills, which is also one of the vital aspects of data science.\n\n\n\nShe also added that when it was about the learning phase she has learnt fundamentally on the job. And apart from that, videos, data science blogs, peers and team members have been the source of knowledge for her. She also believes that when it comes to training, practice is one of the not-to-ignore things in data science. \u201cImmense amount of practice in applying techniques to real-world problems has been my best training,\u201d Mathangi added.\n\n\n\nThis Is How Mathangi Handles Setbacks\n\n\n\nSetbacks are not always in the form of failures but sometimes it\u2019s also in the form of feeling \u2014 mostly self-doubt \u2014 that you get at a certain point of time. And data science professional experience this feeling at least once in their career.\n\n\n\nAll data scientists suffer from the Imposter Syndrome at least once in their careers.\n\n\n\nImposter syndrome is one such feeling that is common with data science professionals. And Mathangi often suffers from this. \u201cI do feel I am an outsider faking it,\u201d said Mathangi. She also believes that this syndrome only goes up with experience and never comes down. However, she often tries to be as much hands-on as possible, which she believes is one way of combating the syndrome. \u201cI am not sure if I have figured out how to deal with it except sometimes ignoring it and just get going with the job at hand,\u201d said Mathangi.\n\n\n\nAnother setback is interview rejections. When we asked Mathangi about her take on this she said, \u201cRejection does feel hard.\u201d And it feels really hard to handle when someone puts in tremendous efforts. But she also believes that without rejection there are no milestones that can be achieved. \n\n\n\n\u201cSometimes rejections are also a blessing in disguise \u2014 when things don\u2019t work out they are generally for the right reasons.\u201d\n\n\n\nThe Best And Worst Experience\n\n\n\nWhile Mathangi talked about her data science journey, she also shared her best and worst experience in the domain. She said that one of the best experience was when they built text mining platform during her days at 7.ai. The platform was built for those with a text mining need and this platform would help them self serve. Further, she is also very excited about some of the personalisation work that she and the team is doing currently at PhonePe.\n\n\n\nTalking about the worst experience, she said, \u201cNot every idea, project or a predictive solution gets implemented in data science. So there are many casualties from that perspective. I would not say this is the worst experience or something but I do think this is something that needs to change.\u201d\n\n\n\nA Piece Of Advice For Aspiring Data Scientists\n\n\n\nThe PhonePe data scientist has also shared some of the advice that she would like to give the aspiring data scientists. She said that one of the best ways to work is by putting data and business at the forefront. She also believes that patience is understated. But this is a virtue that will take one far.\n\n\n\nMoreover, she also added that the way data science gets adopted across organisations, there is a lot of stakeholder understanding that needs to be built. Unfortunately in academia, stakeholder management part of data science is not addressed. There are a lot of sensitivities to take a predictive solution to live in large organisations. The data scientists have to understand the business nuances to succeed.