Work Experience

Infiswift Technologies

• Designed and implemented an automated LinkedIn lead Generation system achieving 30% reduction in human efforts by optimizing the data processing pipeline, using Python and Selenium.
• Generated comprehensive reports summarizing emerging trends in the tech industry, achieving a 25% reduction in time-to-action on insights.

Prifina Inc.

• Constructed a robust statistical model to generate synthetic data by identifying suitable probability distribution for transformed real data sourced from wearable applications, achieving an impressive 85% accuracy rate.
• Designed and executed ETL (Extract, Transform, Load) pipelines to efficiently extract and process data from 8+ wearable applications, including Garmin, Fitbit, and Oura, through Python REST APIs.
• Collaborated with cross-functional teams to gather data and requirements, ensuring 100% alignment with project goals.

Madras Global

• Led and managed an Agile team of three to develop a feature-rich media application, enabling tracking of metric, ad publishing, scheduling, and modification on Google and Facebook advertising platforms.
• Collaborated seamlessly with cross-functional teams to automate more than ten critical workflow services for internal and external clients. Incorporated valuable feedback from stakeholders and customers to enhance application functionality.
• Pioneered design and implementation of a serverless cloud Python automation pipeline to efficiently extract files and metadata from zip files uploaded to AWS S3, resulting in a 70% improvement in client-side rendering and overall operational efficiency.
• Automated full-stack process by building RESTful APIs, applying Django framework, ReactJs and SQLite, empowering users to request changes and annotate media assets through an online proofing tool.
• Remodeled Django framework, following MTV architecture, to run ReactJS at template layer within a single server, optimizing resource utilization and reducing deployment time by 30%.

Madras Global

• Developed scripts to extract, scrub, analyze and visualize datasets for predictive modeling with Django framework, SQLite, and Python.
• Programmed python automation scripts to scrape hourly and process 500K+ records for sentiment analysis.
• Automated full-stack process by creating restful APIs using Django and ReactJs, reducing manual effort by 80%.