Vijeta Prakash
About Vijeta Prakash
Vijeta Prakash is an Associate Consultant Data Scientist at KPMG India, with a Master's degree in Computer Science from the University of Hyderabad. She has expertise in anomaly detection, predictive repairing, and various data analysis techniques, and has experience working with AWS and Azure services.
Work at KPMG India
Vijeta Prakash currently holds the position of Associate Consultant Data Scientist at KPMG India. She has been with the company since 2022 and is based in Bengaluru, Karnataka. In her role, she engages in various data science projects, applying her expertise in machine learning and data analysis to deliver insights and solutions.
Education and Expertise
Vijeta Prakash earned her Master's degree in Computer Science from the University of Hyderabad, where she studied from 2019 to 2021. Prior to that, she completed her Bachelor's degree in Computer Science at the Kalinga Institute of Industrial Technology from 2015 to 2019. Her academic background provides a strong foundation for her work in data science and machine learning.
Background in Data Science
Before joining KPMG India, Vijeta worked at Prudent Technologies and Consulting, Inc. as a Data Scientist from 2021 to 2022. She also served as a Data Science Intern at the same company earlier in 2021. Her experience includes contributions to projects focused on Anomaly Detection and Predictive Repairing using Time Series data.
Technical Skills and Tools
Vijeta possesses practical knowledge in various data science techniques, including Sequence Classification, Named Entity Recognition, Text Summarization, and Topic Modeling. She is experienced in wrapping applications using Flask for API testing and has utilized tools like Postman and Pytest for unit testing. Additionally, she is adept at using Plotly Dash for data analysis and is familiar with PowerBI for data visualization.
Cloud Services Experience
Vijeta has extensive experience working with cloud services, particularly AWS, where she has utilized EC2 and S3 buckets for project requirements. She is also familiar with Azure API services, which she has applied in her data science projects to enhance functionality and performance.