Vipul Tanwar, Cqf
About Vipul Tanwar, Cqf
Vipul Tanwar is a Quantitative Researcher currently employed at HSBC in Bengaluru, Karnataka, India. He has a background in quantitative finance, with previous roles at Ola, iRageCapital, and Edelweiss, and holds a Certificate in Quantitative Finance.
Current Role at HSBC
Vipul Tanwar currently serves as a Quantitative Researcher at HSBC, a position he has held since 2022. He works in Bengaluru, Karnataka, India, contributing to the bank's quantitative analysis and research efforts. His role involves applying advanced statistical methods and machine learning techniques to develop trading strategies and enhance financial models.
Previous Experience at Ola
Vipul Tanwar worked at Ola (ANI Technologies Pvt. Ltd) as a Financial Analyst in two different capacities in 2015. He served as a Financial Analyst for the East Zone for six months and later as a Financial Analyst for Ola Share for an additional six months. His work during this period focused on financial analysis and operational support within the organization.
Educational Background at IIT Kanpur
Vipul Tanwar graduated with a Bachelor of Technology (BTech) in Mechanical Engineering from the Indian Institute of Technology, Kanpur, in 2014. IIT Kanpur is recognized for its rigorous engineering programs and has a strong reputation in the academic community. His education provided a solid foundation in engineering principles and analytical skills.
Professional Qualifications in Quantitative Finance
Vipul Tanwar holds a Certificate in Quantitative Finance (CQF), which is a professional qualification aimed at individuals in the quantitative finance sector. This certification demonstrates his expertise in quantitative analysis, financial modeling, and algorithmic trading, enhancing his professional credentials in the finance industry.
Technical Skills and Expertise
Vipul Tanwar possesses strong programming skills in languages such as Python and C++, along with expertise in Q/Kdb, which is utilized in high-frequency trading environments. His comprehensive understanding of statistics and machine learning further supports his work in quantitative analysis and the development of algorithmic trading strategies.