Professional Summary
Prashant is an accomplished executive leader specializing in building and deploying large-scale data and machine learning products. His career spans leadership roles at **Microsoft, Google, and JP Morgan Chase**, culminating in his current focus on driving innovation with Generative AI and agentic workflows.
His expertise includes architecting cloud-native AI solutions, establishing robust data governance and privacy practices (including differential privacy), and translating complex data science into measurable business outcomes across finance, search, cloud, and engineering domains.
Core Expertise
Generative AI & LLMs
ML Engineering & Ops
Data Governance & Privacy
Data Product Strategy
Advanced NLP
Cloud Architectures (Azure/GCP)
Deep Learning (RNN/CNN)
Experimentation & A/B Testing
Domain Expertise
Banking
Stocks and Investment
Tax and Financial Planning
Supply Chain
Industry 4.0
Data Signal
Career Highlights
Feb 2023 – Present
Chief Data Science & Technology Officer, DataKnobs
- Spearheading Generative AI product development (KREATE suite for website/bot generation).
- Defining the vision and strategy for end-to-end Data Product creation and governance.
2019 – 2022
Managing Director, Machine Learning & Engineering
- Led teams to build transformative ML products and analytics solutions across the financial sector.
- Pioneered methods for handling data privacy and governance for ML applications in high-confidentiality environments.
2016 – 2019
Data Science Leader, Google
- Key role in the Google-Kaggle acquisition; architected secure ML competitions on highly confidential data on Google Cloud.
- Defined the Google vision for Industry 4.0 (ML for manufacturing) and led predictive maintenance solutions.
2004 – 2016
Director / Principal, Microsoft
- Built the Audience Intelligence Platform for Bing, used for behavioral targeting across all Microsoft properties (Bing, MSN, Hotmail).
- Contributed to products including Azure ML, Bing, and SQL Server.
Selected Projects & Contributions
KREATE: Generative AI Suite
DataKnobs
A set of products for generating full websites, AI assistants, and enterprise bots, demonstrating practical GenAI application in product development and automation.
Financial Earning Call Analysis & NLP to SQL
JP Morgan Chase, Google
Developed advanced NLP models for deep analysis of corporate financial reports and a system to translate natural language queries directly into SQL for data retrieval.
Streamflow Hydrology Estimate (SHEM)
National Water Center (NWC/NOAA)
Designed and built an ML model for real-time flood forecasting using stream gage data, contributing a published chapter on the solution in a NOAA book.
Secure AI Experimentation
Google Cloud
Architected the framework to run ML competitions on highly sensitive and anonymized data, setting industry standards for data science in regulated industries.