Sowjanya M
Data Scientist @T-Mobile
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WORK HISTORY
Data Scientist @T-Mobile
TX, US
Developed AI chatbot with retrieval-augmented generation (RAG) using OpenAI & AWS Bedrock, improving customer query resolution by 35%.• Fine-tuned domain-specific LLMs (LLaMA, Mistral) with LoRA, reducing hallucination rates by 20%.• Built NER pipelines using SpaCy & AWS Comprehend, extracting key telecom entities to enhance chatbot context.• Orchestrated workflows with AWS Lambda & Step Functions, ensuring scalable, serverless operations.• Implemented real-time analytics dashboards with CloudWatch, improving AI system monitoring.• Integrated chatbot with CRM, billing, and backend APIs using FastAPI, improving response time by 25%.• Conducted A/B testing on chatbot versions, optimizing user engagement and conversion rates.• Led cross-functional workshops to train teams on AI system usage and collect feedback for continuous improvement.• Improved chatbot intent detection accuracy by 15% through enhanced entity recognition and domain specific fine-tuning.
EDUCATION
Central Michigan University
Master's
Amrita Vishwa Vidyapeetham
Bachelor of Technology - BTech
ABOUT SOWJANYA M
Data Scientist with 5 years of experience delivering machine learning (ML) and advanced analytics solutions across telecom, healthcare, and retail domains. • Skilled in developing and deploying ML/DL models using Python, R, SQL, and cloud platforms like AWS, Azure, GCP. • Hands-on expertise in Natural Language Processing (NLP), predictive modeling, deep learning, and retrieval-augmented generation (RAG) for chatbot development. • Experienced in end-to-end data science workflows: data cleaning, feature engineering, model training, evaluation, and production deployment. • Strong knowledge of MLOps practices: automated pipelines, model retraining, cloud orchestration (AWS Lambda, Step Functions, Docker, Kubernetes). • Proven ability to work with cross-functional teams, communicate data insights to stakeholders, and drive data-driven decision-making. • Passionate about turning complex datasets into actionable insights, improving business outcomes, and staying updated with cutting-edge AI/ML techniques.
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