Prashant Linkedin Profile
PRASHANT |
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Name: Prashant K Dhingra Author of Generative AI Finance paper.
Building Data Products using Generative AI, AI, knobs at DataKnobs, Ex-Microsoft, Google, JP Morgan Chase.
Redmond, Washington, United States.
Contact: prashantkdhingra@gmail.com
www.linkedin.com/in/
prashantkdhingra (LinkedIn)
prashant.dhingra.website
(Personal)
Top Skills: Data Governance
Large Language Models (LLM)
Generative Components
Honors-Awards: Microsoft Gold Star
Microsoft Gold Star
Architecture for complex mobile application
Growing customer account and team
IP/Innovation award at Google
Languages: Hindi (Native or Bilingual)
English (Full Professional)
Certifications: Exploratory Data Analysis
The Data Scientist’s Toolbox
R Programming
Bachelors's degree - Diploma in business management
Machine Learning
Publications: Approaches for email classification
SQL CE Tools
SQL Server Compact Edition
Streamflow Hydrology Estimate Using Machine Learning (SHEM)
Earning call summarization - template aware attention model
Summary: Experience Summary
May 2022 - Chief Technology Officer, Startup(s)
2019 - 2022: Managing Director (Machine Learning and Engineering)
2016-2019 : Data Science Leader at Google.
2004-2016 : Director/Principal at Microsoft
1993-2004 : Architect and engineering lead in consulting companies.
I am building Data products. My team includes - Data Scientists,
Machine Learning Engineers, Full stack developers, data engineers,
product managers and architects.
Prior to Pluto7/startup(s) I worked as Managing Director for Machine
Learning & Engineering. I built transformative machine learning
products, data products and analytics solutions.
Prior to joining JP Morgan Chase, I led data science initiatives
at Google. I played a key role in Google Kaggle acquisition and
architected how data science competitions can be run on highly
confidential data on Google Cloud.
At Microsoft, I worked on Azure ML, Bing, and SQL Server
products. While working for bing.com I built an Audience intelligence
platform for Microsoft. Audience intelligence platform is used for
Behavioral Targeting on all Microsoft properties such as bing.com,
msn.com, Hotmail, etc.
I wrote a book on SQL Server and a chapter on machine learning in
NOAA book.
I also have expertise in handling data privacy, governance,
differential privacy, cyber security, and applying machine learning for
Displaying content on multiple web
pages
Event based Ad Targeting
user/audience data. I have certification in handling data privacy and
differential privacy.
Experience: DataKnobs | Chief Data Science & Technology Officer | February 2023-Present(1 year) | Seattle, Washington, United States
Built following products
kreatewebsites.dataknobs.com - To generate websites
kreatebots.dataknobs.com - To generate bots
dataproduct.dataknobs.com - To build e2e Data products
abexperiment.dataknobs.com - AB Experiment on Data Products
2023 - I am working with startups to deliver generative ai, ab testing and
integrate machine learning into data products. Built a product related to
generative AI and capabilities to add compliance in generative AI.
Built Chatbot using ChatGPT, OpenAI
2022 - Worked as CTO/CDO and built an intelligent supply chain for Startup.
It includes Demand Sensing, Raw material forecasting, Smart Factory,
Distribution Requirements Planning, and Inventory positioning.
Technologies used - Machine Learning, Data, Google Cloud Platform, Azure,
AWS, SAP
Leader for data scientists, cloud engineers, architects, and customer success
managers
HIVE TA Technologies Inc. | Chief Data Science & Technology Officer | September 2023-Present(5 months)
Build Chatbot for Tax and financial Planning
Supply Chain startup | Chief Technology Officer | May 2022-February 2023(10 months)
Build AI solution on GCP - forecasting, demand sensing
JPMorgan Chase & Co. | Managing Director ( Machine Learning and Engineering) | January 2019-May 2022(3 years 5 months) | Greater Seattle Area
Prashant delivered
1. Built data products e.g. Earning call, stock signals, NLP-SQL (Earning call
generates summary of earning call, Built using Transformer. NLP to SQL
generate SQL code)
2. Transformative Machine Learning use cases across firm
3. Provide thought leadership, define and deliver innovative products.
AI Product I defined. include Earning-call analysis, NLP-to-SQL,
PrivacyIdentification, data quality.
Machine Learning use cases include
Example of use cases, Prashant team deliver
A. Stock signal for high-frequency trading: Determine stock price direction and
use it for order placement for S&P500 and STOXX600 stocks.
B. Simulator for stock trading. Reinforcement learning framework for stock
trading.
C. Customer feedback, sentiment analysis
D. Models to find anomalies in cyber data
E. Payment prediction and claims model(s)
F. Stock buyback
Google | Data Science Leader | December 2016-January 2019(2 years 2 months) | Greater Seattle Area
Prashant Acted as head of Machine Learning practice in USA and in Canada.
Led many data science initiatives at Google.
Prashant defined Google vision for Industry 4.0 (machine learning for
manufacturing)
Worked on Google Kaggle acquisition. Led Google Kaggle Caesars initiative
(3 company initiative). It proved how to anonymize and secure highly
confidential gambling data and run the Kaggle competition on Google Cloud
AI.
Organize first Kaggle competition on Google Cloud. Played a key role in the
Google-Kaggle acquisition.
A. ML to improve English in documents: (Generative AI - generate medical
papers)
B. Predictive Maintenance: Designed generic predictive maintenance solution
using IoT signals
C. Smart cities and streets: Build model(s) to identify road conditions and
objects on streets.
D. Vehicle usage determination: Based on IoT data, determine the purpose of
vehicle use.
E. Visual anomalies - using photos to determine damage from car accidents.
(Use generative AI to generate dataset for model training)
5. Airport and aircraft saftey related model.
6. Route prediction
7. Predict which back up job will fail
8. Predictive maintenance
Expertise in :
Recurrent Neural Network (RNN), Convolutional Neural Networks (CNN),
Deep Learning, AutoEncoder model architecture.
TensorFlow, CloudML, Cloud AI platform
Microsoft
12 years 3 months
Principal - Azure Machine Learning | May 2014-December 2016(2 years 8 months) | Redmond
I have worked on Bing Machine Learning, Azure Machine Learning and SQL
server team.
In Azure ML, worked on ML platform. In addition deliver these data science
use cases:
A. Led the development of the "Opportunity scoring" model that was shipped
with Microsoft CRM.
B. Sales and Marketing Model. - My team has built and deployed variety of
Sales and Marketing machine learning models - to identify new customers,
cross sell, upsell, churn, customer segmentation topics.
C. Flood Forecasting for National Water Center
Imagine how many lives can be saved if we predict flood before rain start. I
have worked with NFIE (National Flood interoperability experiment) to build
flood forecasting solution.
I have designed and build ML Model to predict water thru Stream Gages.
NFIE went live at NWC (National Water Center). Case study is published in
NOAA book. My research paper is accepted in Hydrology Journal.
Director Microsoft (ML and Cloud) | February 2011-April 2014(3 years 3 months) | Greater Seattle Area
Worked in the "Enterprise Strategy and Architecture" group.
Also build a machine learning model that identifies document/IP reuse.
Lead - BingAds Machine Learning models | November 2008-February 2011(2 years 4 months)
Worked on www.Bing.com/AdCenter in “Revenue and Relevance” Microsoft
US.
Led development in Microsoft Yahoo integration
Click Prediction (Adpredict), Smart match, auction pricing,
Led development of Behavioral targeting platform and audience intelligence
store.
Lead AdLab Research - Behaviroal targeting models platform | 2008-2010(2 years)
Build Algorithm publishing framework for Audience intelligence.
Built audience intelligence platform. Built personalization capabilities.
Algorithm determine which "advertisement/recommendation" should be shown
on Hotmail users.
Algorithm/Experiment published for Behavior Targeting on Hotmail, Bing, MSN.
Principal GPM - Analytics | October 2007-October 2008(1 year 1 month)
Group Program Manager of BI group (BI Center of excellence and delivery) in
Microsoft India
Lead - SQL Server | October 2004-October 2007(3 years 1 month)
Hyderabad Area, India
Lead and Product Manager for "SQL Server Compact Edition"
Wipro Technologies | Solutions Architect | 2003-2004(1 year)
Architected big mobile application HH3 for Pepsico/Frilolay
This application has 300 forms on a mobile device. It covers customers, order
management, inventory management, sales order, promotions functionality of
PepsiCo/Fritolay.
Steria Group | Software Engineering Lead | February 1994-October 2003(9 years 9 months)
Architect for Halifax bank and Bank of scotland
Dev Manager/Architect of NSPIS – National strategy for Police Information
System
Dev Lead for Unitied utilities project.
Between 1994-2003 I worked for Steria Group (known as IIS InfoTech). During
these years I saw growth from 80 employee company to 2000 employee
company. For almost 10 years I worked on various customer sites. While
working for IIS, I built many teams and managed customer relationships for
multi-million GBP.
Softek India | Assistant Engineer | July 1993-February 1994(8 months)
Worked on testing of Fortran compiler
Education: University of California, Berkeley
Master of Science - MS,Data Science
Maharshi Dayanand University
Engineer’s Degree,Computer Science·(July 1989-June 1993)
Quantic School of Business and Technology
Executive MBA ,Finance, General·(2019)
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