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Pranav N.

Pranav N.

N L P · Mid-level

Available profile

Professional Overview

I'm a Master’s graduate who has been working in the field of Machine Learning for over 7 years. I did my Bachelor's as well as my Masters by Research in Artificial Intelligence (specifically, multimodal data) at India’s top research institute - IIIT-Hyderabad.Corporate:In 2018, I founded and ran my own Data Science Consultancy called WhyNot? Technologies where I led teams and worked as a Data Scientist on projects for multiple Fortune 500 companies like Audi Germany, Reliance Gas and Oil, and Lionbridge (A project for Microsoft (NLP) Cortana)! I’ve helped them save over $600 Million by building proprietary data algorithms. I have over 7 years of experience in Pytorch + Fairseq + FastAI.Research:My scholarly endeavors have seen me collaborate with three distinguished academic labs: LTRC (Language Technology and Research Center), CVIT (Computer Vision and Image Technology), and DSAC (Data Sciences and Analytics Center), where I explored multiple state-of-the-art problem statements and solutions with a special emphasis on Natural Language Processing (NLP) and Computer Vision. My contributions to these fields have been recognized and shared at international conferences, where I have published two papers elucidating my findings and research.Data Science models are rarely domain-specific and are surprisingly usable across multiple problems, over multiple domains. Hence by knowing most state-of-the-art models across all major fields - thanks to my research as well as corporate involvement with the same - I can say confidently that I can tackle problems in most domains.

Areas of Expertise

NLP & Prompt Engineering

Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.

AI & Machine Learning Engineers

Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.

data science & analytics

Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.

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