Himanshu Pant
About Himanshu Pant
Himanshu Pant is an Assistant Manager at IndusInd Bank with expertise in predictive modeling and data analysis. He has a diverse background in finance, technology, and management, with previous roles at ICICI Prudential Life Insurance and GSPC LNG Limited.
Current Role at IndusInd Bank
Himanshu Pant currently serves as an Assistant Manager at IndusInd Bank, a position he has held since 2019. He is based in the Faridabad Area, India. In this role, he is responsible for supporting managerial decision-making by retrieving and analyzing data from various sources, which aids in providing strategic insights for the bank's operations.
Previous Experience at ICICI Prudential Life Insurance Company
Prior to his current role, Himanshu Pant worked at ICICI Prudential Life Insurance Company Limited as an Assistant Manager for four months in 2019. He also held the position of Management Trainee at the same company from 2018 to 2019 for eight months. Both roles were based in Vadodara, Gujarat, India, where he gained valuable experience in the insurance sector.
Internship Experience at GSPC LNG LIMITED
In 2017, Himanshu Pant completed a summer internship at GSPC LNG LIMITED for four months. This experience provided him with insights into the energy sector and contributed to his professional development.
Educational Background
Himanshu Pant has a diverse educational background. He earned a Bachelor of Technology (BTech) in Computer Science from Kurukshetra University from 2010 to 2014. He then pursued a Master of Business Administration (MBA) in Energy and Infrastructure Management at the School of Petroleum Management from 2016 to 2018. His foundational education includes a High School Examination from Aggarwal Public School, completed from 2002 to 2007, and secondary education at Tagore Academy from 2007 to 2009.
Technical Skills and Projects
Himanshu Pant possesses strong technical skills in data analysis and machine learning. He builds predictive models using algorithms such as logistic regression and K-Nearest Neighbors (KNN). He utilizes tools like Jupyter Notebook and IPython for data pre-processing. Notably, he conducted a data regression analysis that improved the accuracy of performance predictions by 5% compared to previous years.