Digital loans and savings company Shubh Loans has announced the appointment of Dr. Venkatesh Madyastha as the Chief Data Scientist.
Venkatesh is a data scientist with 13+ years of experience in research and data analysis. Before joining Shubh Loans, he was a principal data scientist with the data science R&D team at the Shell Technology Center, Bangalore, India, where he worked on the design, development and deployment of machine learning-based predictive models for a variety of Shell assets. He led a team that successfully deployed, in real-time, a monitoring tool for anomaly detection of two Shell assets. Venky holds a Ph.D. in aerospace engineering from the Georgia Institute of Technology, Atlanta, Georgia, USA.
Venkatesh’s role includes applying advanced algorithms to complex problems in real-time systems which would help deliver concise, insightful analysis that can be put to operational use for better results. Also, drive the innovation and improvement of Shubh Loans product through cutting edge data-driven analysis. His leadership with a strong analytical background will steer the company’s deep data science driven credit-scoring model to deliver a smooth user experience.
“We have set up Data Science – “Centre of Excellence” with best professionals from across the globe, Venkatesh’s domain expertise with academic excellence will add tremendous value to this initiative. We are committed to taking financial services to the next billion and this is another step in that direction.” said Monish Anand, CEO and Founder, Shubh Loans.
Being India’s next-gen credit scoring and lending platform, Shubh Loans’ strength is in data sciences because it believes that the lending model is key to superior customer experience. Venkatesh is geared to lead the Data Sciences Centre of excellence at Shubh Loans which includes PhDs from top institutions.
Sharing his view about joining Shubh Loans, Venkatesh says, “I enjoy working on cutting edge technology intending to push the boundaries of innovation. At Shubh Loans, my role is to use the power of data combined with existing scorecards to address the financial needs of a section of the society who are oftentimes excluded from the conventional banking sector.”