Prasang Biyani

About Prasang Biyani

With over five years of experience in AI and ML, I specialize in building scalable, high-impact machine learning solutions that drive business value. I have a strong background in predictive modeling, recommendation systems, NLP, and edge AI deployments. At Accenture, I have led the development of ML-driven bid-winning prediction models, word2vec-based recommendation engines, and MLOps pipelines, enabling seamless deployment and automation of AI workflows. Previously, at Matrix ComSec, I optimized deep learning models for edge devices, implementing real-time face recognition and license plate recognition. My expertise spans LLMs, Transformers, CNNs, vector databases, and MLOps, with hands-on experience in TensorFlow, Scikit-Learn, Keras, Weaviate, and Python. I am passionate about applied AI research, model optimization, and building AI solutions that scale efficiently in production. My curiosity also leads me to explore cutting-edge fields like Quantum Biology, where computational models can unravel complex biological mysteries at a fundamental level. I enjoy sharing my knowledge through technical blogs on Medium and open-source contributions on GitHub. Let’s connect to discuss cutting-edge AI innovations! Portfolio & Projects: github.com/prasangg | medium.com/@biyaniprasang Reach out to me: b••••••••@gmail.com

Experience

1. Data Scientist

   Accenture

   Jul 2021 — Present · Pune, IN

   Developed AI-driven bid-winning prediction models using XGBoost, achieving 95% precision and 93% recall, improving deal strategy decisions.Built a word2vec-based recommendation engine to suggest high-probability deals, optimizing business growth.Designed and implemented end-to-end MLOps pipelines for model evaluation, tuning, and automation using Scikit-Learn, GitHub Actions, and Azure CI/CD.Deployed machine learning models and recommendation systems using Flask APIs on cloud platforms, ensuring scalability and real-time performance.Led API service development to enable seamless integration across teams, enhancing collaboration and deployment efficiency.Engineered a Flask-based text extraction API for unstructured data (PDFs, PPTs, and scanned images), improving data processing efficiency.Designed an AI-powered financial insights dashboard to summarize key financial KPIs and provide actionable improvement recommendations. Tech Stack: Python, TensorFlow, Scikit-Learn, XGBoost, Pandas, NumPy, Flask, Azure CI/CD, MLOps, NLP, Word2Vec

Education

• CHAROTAR UNIVERSITY OF SCIENCE AND TECHNOLOGY

  B.Tech

  2013 — 2017

• Scaler

  Master of Science in Computer Science: Artificial Intelligence and Machine Learning

  2022 — 2023

Skills

• Research
• C++
• C
• Programming
• Computers Enthusiast
• Cryptography
• Machine Learning
• Microsoft Word
• Management
• Intel 8085
• Matlab
• 8051 Microcontroller
• Project Management
• Leadership
• Process Improvement
• Training
• Powerpoint
• Microsoft Excel
• Microsoft Office
• Keil