🚀 Lead Data Scientist | NLP & Computer Vision Expert | 3 Patents | Fintech Innovator I am currently a Lead Data Scientist at Paytm, India’s leading fintech platform, where I design and deploy large-scale AI solutions that directly impact millions of users. With years of experience at the intersection of Machine Learning, Deep Learning, and Applied AI, I specialize in Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Cost Optimization. 💡 Key Highlights: Expert in NLP & Computer Vision: Published research and holder of 3 patents in these domains. Applied AI in Fintech: Building scalable models for fraud detection, personalization, and customer experience at Paytm. Strong Coding & System Design: Python as my core language, complemented by Java, JavaScript, and C++ for full-stack data science solutions. Data Engineering & Analytics: Skilled in SQL with hands-on experience in MySQL, PostgreSQL, MongoDB, and BigQuery for high-volume data handling. API Development & Deployment: Proficient in Python frameworks (Flask, Django, FastAPI) for creating production-grade AI services. 🔍 What I Do Best: I bridge the gap between cutting-edge AI research and real-world business impact. Whether it’s designing NLP pipelines for text understanding, building computer vision systems for recognition and detection, forecasting business trends with time-series models, or driving cost optimization using ML, I create solutions that scale. 🌐 Why Connect with Me? You’ll gain insights from someone who has designed AI systems at enterprise scale in one of the fastest-growing fintech ecosystems. I bring a research-driven yet practical approach, ensuring solutions are both innovative and implementable. Passionate mentor and guide for professionals and students aspiring to excel in Data Science, NLP, and Computer Vision. 📌 Let’s connect if you want to: Build expertise in NLP, Computer Vision, or AI deployment. Understand how to scale ML/AI in fintech, e-commerce, or real-world applications. Get mentorship in designing projects, cracking interviews, or transitioning into senior data roles.