Rampraveen Chamarthi
About Rampraveen Chamarthi
Rampraveen Chamarthi is a Quantitative Analyst at BioUrja Group in Hyderabad, India, specializing in financial electricity products across various Independent System Operators. He holds a Bachelor of Engineering in Mechanical Engineering from BITS Pilani and has also studied Finance.
Work at BioUrja Group
Rampraveen Chamarthi has been employed at BioUrja Group as a Quantitative Analyst since 2020. His role involves developing optimization and pricing models that utilize Python and SQL, reflecting the physical fundamentals of Independent System Operators (ISOs) markets. He specializes in financial electricity products across various ISOs, including ERCOT, NYISO, and SPPISO. His responsibilities also include conducting research on weather patterns, congestion trends, and grid protocols to improve data-driven models.
Education and Expertise
Rampraveen Chamarthi earned a Bachelor of Engineering (BE) in Mechanical Engineering from BITS Pilani, Hyderabad Campus, from 2016 to 2020. He also pursued a minor in Finance at the same institution from 2018 to 2020. Prior to this, he completed his Intermediate education at Sri Chaitanya College of Education, focusing on Mathematics, Physics, and Chemistry (MPC) from 2014 to 2016. His educational background provides a strong foundation for his expertise in quantitative analysis and financial modeling.
Previous Work Experience
Before joining BioUrja Group, Rampraveen Chamarthi worked as a Design Engineer at UST for a brief period of two months in 2018, based in Thiruvananthapuram, India. He then transitioned to a role as a Credit Structuring Analyst at Nomura, where he worked for six months in 2020 in the Mumbai area. These positions contributed to his development in engineering and finance, enhancing his analytical skills in quantitative analysis.
Technical Skills and Tools
In his current role, Rampraveen Chamarthi utilizes various technical tools and programming languages to support his work. He develops optimization and pricing models using Python and SQL, and employs optimal power flow modeling tools such as PowerWorld, DAYZER, and Panorama. His technical skills enable him to manage and analyze data from ISOs effectively, allowing for accurate predictions of prices and congestion in electricity markets.