Bachelor of Technology - BTech

Master's degree

• Architected and deployed end-to-end machine learning pipelines on Amazon SageMaker, S3, EC2, and IAM, enabling automated model training and deployment for internal projects
• Implemented supervised and unsupervised learning algorithms for classification and clustering workflows.
• Created computer vision and natural language processing prototypes using OpenCV and Amazon Lex.
• Applied cloud security, scalability, and cost optimization standards in production style environments.

AWS AI and Machine Learning Virtual Intern

• Applied machine learning techniques, including lead scoring, customer segmentation, and workflow optimization, within a production CRM platform, validating model impact through A/B testing to support data-driven business decisions.
• Engineered backend systems and automation pipelines with event-triggered logic, rule-based processing, and approval workflows to operationalize predictive and business logic, reducing manual effort across multiple workflow stages.
• Designed role-based access control and configurable permission systems alongside API integration and database architecture for real time customer engagement.

Software Engineer (Data and ML Applications)

• Designed and implemented time series forecasting models using Fourier Analysis Networks and cross-learning techniques, improving prediction accuracy by approximately 20% .
• Processed and validated over 500,000 ecological records from GPDD and BioTIME using Python scripts with Pandas and automated anomaly-detection workflows in Docker, which reduced data-cleaning time by about 30%
• Developed visualization systems to compare predicted and observed trends, enabling faster performance evaluation.
• Conducted quantitative evaluation using MAE and RMSE to support research-grade hindcasting analysis.

Data Science Research Assistant

Data Scientist / ML Engineer open to new roles | MS Data Science | Python, SQL, AWS

github

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