Abinash Chaudhury

Strategized and coordinated end-to-end Automation testing activities. Assisted in internal/business AI/ML projects and POCs. Focused on enhancing precision, custom performance, speed, and consistency of ML models (Regression, Classification, Clustering, Bagging, Boosting, Recommendation Systems) using Scikit-learn, NumPy, Pandas, Seaborn, matplotlib, and Deep Learning. Developed systems for Speech Sentiment Analysis, Sentiment Analysis using BERT, Fake News Detection, Driver Attention/Safety mechanism, Face Detection (PyTorch), and Forest Fire Detection (YoloV8). Achieved 15% increase in prediction accuracy and 10% decrease in prediction time.

Developed optimization algorithms for financial applications (Expenses and Forecasting). Implemented various machine learning techniques (regression, clustering, classification, recommendation) for customer segmentation and expense trend forecasting. Led QA team and deployed document verification mechanism for automated processing and authorization of multiple transactions.

Automated client processes (servers, data, production) and external websites. Developed enhanced testing mechanisms, increasing throughput by at least 30% and reducing remote execution time by 25%. Managed test tracker, requirements, and led a team of 4 members for testing activities.

Automated/authorized transactions related to Title insurance using basic Test Stack. Worked on NLP training, and created multiple test suites (Regression, Integration, UAT).

Tested multiple banking/financial applications in manual and automated modes across various platforms. Coordinated assignments in multiple regional banks across the product lifecycle, including development and support, and UX.

Specialization: Electronic Communication Engineering

Specialization: Electronics and Telecommunication Engineering