Amey Bansode
About Amey Bansode
Amey Bansode is a Data Analyst with a background in Information Technology and Business Analytics, experienced in various data analysis tools and programming languages.
Work at Rystad Energy
Amey Bansode has held positions at Rystad Energy, initially serving as a Junior Analyst from 2021 to 2022 for 10 months. Currently, Amey is employed as a Data Analyst, continuing to contribute to the company's analytical capabilities. Rystad Energy is known for providing data and insights in the energy sector, and Amey's role involves utilizing advanced data analysis techniques to support decision-making processes.
Education and Expertise
Amey Bansode earned a Bachelor of Technology in Information Technology from K J Somaiya College of Engineering in Mumbai, completing the program from 2015 to 2019. Following this, Amey pursued a Master of Science in Business Analytics at the Naveen Jindal School of Management, UT Dallas, from 2019 to 2021. This educational background provides a strong foundation in both technical and analytical skills.
Background
Amey Bansode has a diverse background in data analysis and programming. Prior to joining Rystad Energy, Amey worked as a Business Analyst Intern at WasemeStennett LLC Business Advisors for 4 months in 2021. Additionally, Amey served as a Student Assistant at the University Recreation at The University of Texas at Dallas from 2020 to 2021 for 9 months, gaining valuable experience in a university setting.
Technical Skills and Tools
Amey Bansode possesses a comprehensive skill set in programming and data analysis. Proficient in languages such as SQL, Python, and Java, Amey utilizes various Python libraries including NumPy, Pandas, and Scikit-learn for data analysis tasks. Familiarity with operating systems and databases such as UNIX, Windows, and MongoDB enhances Amey's analytical capabilities. Experience with tools like Google Analytics, MS Excel, Tableau, and Azure ML further supports Amey's data-driven approach.
Projects and Innovations
Amey Bansode has developed a real-time crowd counting system that distinguishes between real and dummy persons, addressing complex scenarios such as partial visibility of heads. Additionally, Amey implemented a Support Vector Classifier for a data mining project aimed at predicting soccer player ratings based on various attributes. These projects highlight Amey's ability to apply analytical skills to practical challenges.