Data Science with 1+ years in Machine Learning & AI
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Highly motivated Associate Data Scientist with 1.1 years of experience in developing and deploying AI/ML solutions. Proven ability to engineer production-grade transformer-based systems, build RAG pipelines with Azure OpenAI, and fine-tune various ML models. Proficient in PyTorch, Python, Docker, and cloud platforms like Azure and AWS, with a strong background in data structures and algorithms.
Bangalore Institute Of Technology
B.E. · Artificial Intelligence and Machine Learning
August 1, 2020 – June 30, 2024
Winmore
Associate Data Scientist
January 1, 2025 – February 1, 2026
Bengaluru, Karnataka, India
Prola Tech
Frontend Developer Intern
March 1, 2024 – July 1, 2024
Bengaluru, Karnataka, India
Elderly Care Application
June 24, 2026 – Present
• Built full-stack Android application with Flask RESTful API backend and PostgreSQL data models; integrated NLP speech recognition and AI-driven automation workflows with authentication and input sanitization across the client-server boundary.
Skin Cancer Detection - Medical Image Classification
June 24, 2026 – Present
• Implemented ResNet50 transfer learning in PyTorch with a custom classification head; wrote the full training loop from scratch — forward pass, loss computation (CrossEntropyLoss), backpropagation, and optimizer step (Adam) — with learning rate scheduling and early stopping. • Applied aggressive data augmentation (random flips, rotations, color jitter) via torchvision.transforms; evaluated with precision, recall, and F1-score; containerized inference with Docker for reproducible deployment on Linux.
View ProjectCultural Fit Analysis
The candidate's academic background in AI/ML, coupled with professional experience as an Associate Data Scientist, aligns well with a Data Science role. The diverse projects, from full-stack Android development with NLP to medical image classification and transformer-based document intelligence, demonstrate a broad interest and adaptability. The use of various cloud platforms (Azure, AWS) and MLOps tools indicates a modern, industry-aligned approach to development and deployment, which is a good cultural fit for fast-paced tech environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate business requirements into technical solutions and collaborate with stakeholders. The experience in deploying production systems suggests a focus on operational aspects and reliability. The detailed descriptions of technical implementations imply a structured and thorough approach to problem-solving.