Prathyusha Matharasi
About Prathyusha Matharasi
Prathyusha Matharasi is a Python Developer with experience in data aggregation and analysis, currently employed at Cambia Health Solutions. She has previously worked at SYSINTELLI SOFTWARE AND SERVICES, LPL Financial, and First Reliance Bank, and holds a Bachelor of Technology in Electrical and Electronics Engineering.
Work at Cambia Health Solutions
Prathyusha Matharasi has been employed at Cambia Health Solutions as a Python Developer since 2022. In this role, she has contributed to the design and implementation of a PySpark-based large-scale parallel relation-learning system. Her work involves building data frames using PySpark on an AWS EC2 cluster to handle big data requests within the organization. This position highlights her expertise in managing large datasets and optimizing data processing workflows.
Previous Experience in Software Development
Prior to her current role, Prathyusha Matharasi worked at several organizations as a Python Developer. She was employed at SYSINTELLI SOFTWARE AND SERVICES PRIVATE LIMITED from 2017 to 2019, where she scraped data from third-party APIs and aggregated multiple data sources for analysis. She then joined LPL Financial from 2020 to 2021, followed by a position at First Reliance Bank from 2021 to 2022. In these roles, she developed Python scripts for data management and utilized various libraries for data processing.
Education and Expertise
Prathyusha Matharasi earned a Bachelor of Technology in Electrical and Electronics Engineering from Gurunanak Institutions Technical Campus, completing her studies from 2013 to 2017. Her educational background provides a strong foundation for her technical skills in software development, particularly in Python programming and data analysis.
Technical Skills and Tools
Prathyusha Matharasi possesses a range of technical skills relevant to her role as a Python Developer. She has experience with data manipulation and analysis using libraries such as Pandas, NumPy, FeatureTools, Missingno, and SciPy. Additionally, she has utilized PyQuery for selecting specific DOM elements when reading HTML5. Her proficiency in these tools supports her work in data cleaning, exploration, and feature engineering.