Rayana’s path to becoming a Data Scientist at a multinational financial technology company wasn’t smooth or scripted — it was built on setbacks, self-learning, and a deepening love for problem-solving.
“I wasn’t a topper. But I was always curious — always asking why and how,” says Rayana Gouda Patil, a data scientist from Hyderabad, recalling his school years. After Class 12, he appeared for every entrance exam — JEE, EAMCET, Karnataka CET — but didn’t score well in any.
“I wasn’t even sure what stream to choose.” He landed in Mechanical Engineering at KSIT, Bangalore — a field he had no real interest in. The early years felt aimless until a college competition in 2018 changed everything.
“We built an All-Terrain Vehicle from scratch. It made me realise how muchIna. loved applying concepts to real-world problems,” said Rayana. That spark led him to Data Science. During placements, he received offers from MNCs as a systems engineer.
“But something didn’t feel right. I knew I wanted to work with data. I’d already begun learning basic coding out of curiosity,” the 27-year-old said. He applied to an American data analytics firm and was rejected. Undeterred, he picked up new tools, learnt coding seriously, and applied again — this time getting in with a modest Rs 3.5 lakh salary.
“I had zero experience. Every day felt like starting over.” In three years, he worked on global projects, learnt SQL, Python, Power BI, and saw his salary grow to nearly five times what he started with. Wanting deeper impact, he targeted product firms — but was rejected over 15 times.
“That’s when I realised adding skills isn’t optional,” he said. He took online courses, mock interviews, and mentorship to prepare. It finally paid off with an offer from his current organisation. Today, he mitigates credit risk using data and is diving into Generative AI.
From failure to fulfilment — Rayana’s story proves passion and persistence go a long way. over five years of experience, Rayana now earns almost nine times more than his first salary as a fresher.