• Managed highly sensitive financial aid data, ensuring compliance with data protection laws.• Extracted and cleaned data for financial aid requests, optimizing data sets for team use.• Created visually engaging reports using Tableau, translating complex data into actionable insights.

Project: AI for Sustainable VM ManagementFocused on optimizing cloud infrastructure management, particularly Virtual Machines (VMs) hosted on Azure, to reduce operational costs and align with the company’s sustainability initiatives. • Responsibilities: • Azure VM Automation: Developed and implemented Python scripts to automate the process of turning VMs on and off based on usage patterns from data provided in CSV files, reducing manual intervention by 90%. This led to significant cost savings (60-70% reduction in operational costs) and up to 79% CPU hour savings. • Data Analysis: Extracted and processed over 1 million data points from Azure VMs in multiple regions, including East US and Japan, conducting in-depth analysis to identify usage trends. • Time Series Forecasting: Applied Snowflake AI to forecast VM usage and energy consumption, optimizing resource management and contributing to energy savings. • Sustainability Leadership: Utilized OpenAI to analyze VM usage patterns and recommend optimizations, which helped reduce carbon emissions as part of the company’s sustainability efforts. Presented findings and technical reports to senior leadership, aligning the project with PTC’s broader sustainability goals. • Cross-functional Collaboration: Worked closely with cross-functional teams to ensure that the automation process was aligned with both technical and business objectives. Documented progress, created technical reports, and communicated project developments to stakeholders.

Excited to embark on my Externship Lab journey with Energy Innovation Capital through Paragon One! Over the next month, I'll dive into the world of clean energy technology, conducting market landscape analysis of emerging energy segments using tools like Excel, Tableau, and SQL. My focus will be on data mining and creating visualizations to identify trends and synthesize insights on venture capital data in the energy sector. This remote, hands-on experience will allow me to apply my skills in real-world projects and contribute to the development of solutions for a sustainable future. Looking forward to learning, growing, and making an impact in the field of energy innovation!#EnergyInnovation #CleanTech #DataAnalysis #ExternshipLab #ParagonOne #RenewableEnergy

Thrilled to begin my Externship Lab journey with IgniteXL Ventures through Paragon One! Starting today, I'll be immersing myself in the world of venture capital, focusing on tech-enabled wellness companies led by female and diverse founding teams. This unique opportunity will allow me to contribute to refining deal-sourcing strategies and communication approaches, all while gaining invaluable experience in a professional setting. Excited to learn, contribute, and grow in this dynamic field!

Project for Wells Fargo -Performed Junit testing for various services and controllers of the Quality Assurance Portal. Was Responsible for Full Stack development and bug fixes in the frontend and backend of the application. Used SQL to maintain and regularly update the client database. Project for Pfizer - Implemented OCRs and NLTK tools to perform extraction tasks. My responsibilities included using Python and NLP techniques to develop the product.

Deployed on live projects for the telecom and billing solutions domain. Developed a churn prediction model for the Billing Hub dashboard for a telecom customer using techniques such as data analysis, data cleaning, and machine learning algorithms like XGBoost, Decision Trees, and Random Forests.Worked on a movie recommender system. Learned how to deal with missing data, and used web scrapping extensively to fill in the missing and incorrect data.Additionally, constructed a Sentiment Analysis system that analyses the nature of the feedback given by customers

Lead a Plant Monitoring System to predict the failure of machinery at factories. Oversaw the designing of an unsupervised spam clustering model using NLP techniques of stemming, lemmatization, and NLP models such as LDA and BERT. Took initiative to develop an end-to-end PDF Text Extraction software for insurance companies using technologies such as BERT, NER, padding, and deep neural networks.Designated as the point of contact for the EdgeML Intern Team. Gained experience in managing and measuring work for the team and providing regular status updates to the company supervisor.