Harnessing the power of data and AI to solve complex problems. Delivering smart, scalable machine learning solutions that drive real impact
I'm an AI Scientist and Data Scientist with 3 years of experience turning complex data into actionable business intelligence. I am a data scientist with a passion for storytelling. I believe that words and data are the two most powerful tools to change the world. Currently an Engineer II at Verizon, I've contributed to significant revenue growth, operational savings, and customer retention through innovative AI-powered solutions.
My passion lies at the intersection of artificial intelligence, machine learning, and real-world problem solving. I specialize in designing and deploying scalable AI systems that don't just sit in notebooks—they transform how businesses operate. From building generative AI chatbots that reduce customer churn to developing deep learning recommendation systems that boost customer retention, I create solutions that matter.
When I'm not architecting AI solutions or diving deep into neural networks, you'll find me exploring the latest in Agentic AI with LangChain or contributing to the AI community through knowledge sharing. I believe in the power of continuous learning—recently completing certifications from Google Cloud and NVIDIA in machine learning and generative AI.
My approach is simple: every line of code should solve a real problem. Whether it's optimizing call routing to improve efficiency or building interactive analytics platforms for anomaly detection, I focus on creating AI that enhances human decision-making rather than replacing it.
I'm energized by challenges that seem impossible at first glance. There's something magical about taking messy, unstructured data and transforming it into intelligent systems that can predict customer behavior, automate complex processes, or uncover hidden patterns that drive strategic decisions.
July 2022 - Present
May 2021 - July 2021
Developed a call capacity forecasting model leveraging ARIMA and stacked models, achieving 89% forecasting accuracy. Optimized call routing and enhanced load balancing, reducing response time and improving efficiency by 14%.
Developed a chatbot-based agent guidance system using Retrieval-Augmented Generation (RAG), enhancing customer support, reducing repeat calls by 11%, and lowering churn by 5%.
Fine-tuned the DistilBERT model to predict customer call intent from transcripts, achieving 70% accuracy. Enhanced Interactive Voice Response (IVR)-driven customer interactions, improving customer experience and reducing resolution time by 30%.
Developed a deep learning–based recommendation system to suggest optimal plan offers to high-risk churn customers, enabling marketing and customer success teams to drive targeted retention strategies.
Google Cloud
Valid till June 23, 2026
NVIDIA
Valid till Nov 10, 2026
National Institute of Technology, Durgapur
Won 1st place by optimizing Scaled Agile Framework (SAFe) Agile workflows using AI-driven automation. Led the design of structured problem statements, developed prompt templates, and designed the architecture to streamline Agile processes.
Recognized for accountability and exceptional innovation that significantly improved workflow efficiency.
Hyderabad, Telangana