PDF Query App
Summary
Developed an AI-powered application enabling users to upload PDF documents and extract information using natural language queries, enhancing document interaction and accessibility.
Enthusiastic and forward-thinking Senior Data Scientist with 2 years of experience in the IT industry, specializing in Data Science and Generative AI. Proficient in leveraging state-of-the-art ML, Gen AI, and NLP technologies to develop innovative solutions, with a strong foundation from IIT Madras. Seeking new opportunities to design and implement cutting-edge generative AI models, transforming ideas into impactful solutions and driving business value.
Senior Data Scientist (Generative AI)
Gurugram, Haryana, India
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Summary
Currently serves as a Senior Data Scientist specializing in Generative AI, developing and integrating advanced AI solutions to enhance business operations and insights.
Highlights
Developed and deployed an autonomous speech recognition agent using OpenAI Whisper and Realtime API for high-accuracy, real-time voice-to-text conversion, enhancing production-ready voice processing solutions.
Integrated agentic AI workflows to enable multi-step reasoning and seamless tool orchestration, optimizing complex data processing and solution delivery.
Utilized Pandas AI and Agentic AI to automate data analysis, generating faster and more accurate insights into customer behavior, sales trends, and market dynamics.
Conducted in-depth marketing analytics for the France market, leveraging data-driven insights to optimize marketing strategies and significantly improve campaign performance.
Software Developer
Noida, Uttar Pradesh, India
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Summary
As a Software Developer, implemented robust AI solutions, focusing on large language models and agentic workflows to drive efficiency and ensure responsible AI practices.
Highlights
Implemented robust Guardrails for LLMs, detecting and mitigating risks such as bias and inappropriate content, reducing compliance incidents by 30%.
Leveraged LLMs and agentic AI workflows to analyze structured and unstructured data, identifying process improvements and deploying autonomous agents, resulting in an 11% reduction in business turnaround time (TAT).
Designed and deployed a Retrieval-Augmented Generation (RAG) question-answering agent, autonomously integrating and synthesizing data from multiple web sources, reducing manual effort by 50% and increasing response accuracy by 15%.
Built a generative AI model using DALL-E 3 for automated text-to-image synthesis, accelerating creative content generation by 40% and reducing design cycle time by 25%.
Led and mentored a team of interns, providing technical guidance in AI and agentic workflows, which resulted in a 25% improvement in intern project completion rates.
BS
Data Science & Applications
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B.Tech
Computer Science and Engineering
Issued By
Langchain Academy
Issued By
Salesforce
Issued By
AWS
Issued By
IIT Madras
Issued By
IBM
Issued By
Various
LangGraph, Crew AI, Langchain, HuggingFace, OpenAI, Simple & Sentence Transformers, Scikit-Learn, SciPy, Spacy, NLTK, Gensim, Statsmodel, Keras, Tensorflow.
Generative AI, Explainable AI, NLP, Deep Learning, Machine Learning, Data Visualization, Data Cleaning & Analysis, Feature Engineering, Model Training, Fine-Tuning, Clustering, Time Series, Anomaly Detection, Agentic AI, AI Agents, RAG, GraphRAG, LLMs (ChatGPT, Llama 2), LLMOps, Prompt Engineering, Transformers (BERT, GPT, XLNet), LSTM, RNN, Random Forest, XGBoost, LightGBM, Linear & Logistics Regression, KNN.
Python, SQL, PostgreSQL, Git, Github, Flask, Streamlit.
AWS, Databricks, Docker, Kubernetes, CI/CD.
Summary
Developed an AI-powered application enabling users to upload PDF documents and extract information using natural language queries, enhancing document interaction and accessibility.
Summary
Developed an AI-powered conversational interface that translates natural language queries into SQL commands, enabling non-technical users to interact with SQL databases.
Summary
Developed a content-based recommender system designed to suggest 5 movies similar to a given movie, enhancing user experience through personalized recommendations.