New York City

Ameya Shanbhag

PM @ Morgan Stanley

+1 (646) 290 - 0134


Date of Birth:

January 10th, 1996

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Hello! I'm Ameya


Outcome-driven product manager with entrepreneurial experience, responsible for leading cross-functional teams to plan, build, deploy, and maintain data warehouse projects across different banking products at Morgan Stanley.

Technical expertise in Deep Learning and Cloud along with hands-on experience in Design Thinking, Roadmap Creation, Strategy Planning & Execution.

I can be reached through my LinkedIn profile or via the contact form below!

Nov 2019 - Present

Product Manager


Morgan Stanley

  • Pioneering the 'Design Thinking' framework for current projects inside Morgan Stanley's banking divison

  • Facilitating a team of 5 people for a critical regulatory reporting project potentially saving the firm $1MM/year in expenses

  • Streamlined the client invoicing and operational process while accelerating accurate reporting for mulit-collateral loan processing which led to the potential increase of $3MM/year in revenue opportunity

  • Storyboarded and visualized a product roadmap for multiple banking products along with their milestones and release timelines thereby increasing the efficiency of delivery planning and time estimation

Aug 2019 - Nov 2019

Business and Data Analyst


Morgan Stanley

  • Formulated a Straight-Through-Processing index for each business process by performing cross-platform analysis as a part of the firm's 'Platform Front-to-back' initiative potentially saving the firm $5MM/year in operational expenses

  • Launched a web dashboard for developing insights and creating reports for the test plans stored by teams at the firm, currently in use by DevOps team

  • Reduced the data processing time by 40% and disk utilization by 80% by formulating a python script which would do parallel processing and data cleaning on-the-fly using multi-threading

Aug 2018 - Present

Adjunct Instructor


NYU Center for Data Science

  • Conducted lectures for the 'Introduction to Machine Learning' graduate-level course and authored lab materials for the same

Jun 2018 - Aug 2018

Technology Summer Analyst


Morgan Stanley

  • Built a referential data retrieval application which will be used by Municipal Bond Traders and Strats in order to make trades and retrieve information for a particular municipal bond

  • Redesigned the application with triggers for different types of municipal bonds which led to an increase in time efficiency by 30% for the municipal bond traders

  • Leveraged Windows Presentation Foundation (WPF) to develop the application in C# and XAML

Feb 2018 - May 2018

Product Data Analyst

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NYU: Office of Dean

  • Responsible for the stakeholder management with the NYU Dean’s office to strategize student retention problem thereby increasing student retention by 25% using data analysis and forecasting

  • Reengineered the university ranking formula and curated an algorithm to estimate the factors affecting NYU Rankings potentially contributing to an improvement in NYU’s World University Rankings from 52nd position (in 2018) to the 35th position (in 2020)

Mar 2017 - Aug 2017



Cafe Enginerd

  • A non-profit organization to re-innovate the process of career selection in the field of engineering for Indian students

  • Co-ordinated with professionals from different industry and students who were eager to contribute to this organization

  • Conceptualized the process and used Google Marketing Tools to expedite the process of reaching out to the mass audience

Jun 2016 - Nov 2016

Software Engineering Intern

Indian Institute of Technology: Bombay

  • Developed different modules for an Android Application using Google Firebase Cloud API to auto generate medical reports

  • Resolved the data passing issue by using AWS Data Pipeline which helped to transfer data from AWS S3 to AWS Dynamo DB

  • Developed an alternative for generating Android files in Python to Java using the Kivy Platform.

Sep 2015 - Nov 2015


Baking Bytes

  • Co-Founded a startup initiated to encourage young entrepreneurs with limited technical knowledge by undertaking their project requirements and objectives and achieve the ultimate business model.

  • A technology solutions group which helped small size local businesses to develop web and android applications thereby generating revenue of $1k/month

Jun 2015 - Aug 2015

Android Developer

CATKing India

  • Developed an Android Application ‘Mia-Mia’ to help users search for anything ranging from salons to hotels to tuition classes. 

  • Integrated Cognalys library, a Multi Platform Mobile Number Verification Library which made mobile verification convenient and hassle-free. 

  • Designed the User Interface using Material Design library which made the application easy and simple to use. 

New York City
New York City

Deep Learning

An application which would take in any voice input, would convert it to Obama's voice and create a video of Obama saying the same thing you gave as a voice input but in Obama's voice


Obama Deep Fake

Sentiment Classification using CNN-LSTM

Performed sentiment classification by using sequence models and is trained on the IMDB Movie review dataset and will learn to classify the sentiment as positive or negative.


Implemented a CNN using PyTorch on the CIFAR10 dataset. The convolutional layers would do the feature extraction, but classification is still being aided by the fully connected layers


Image Recognition using CNN-Pytorch

Vanilla Neural Network

Implemented a fully connected neural network in python using just the matrix operation library The network consists of a minimum of two hidden layers (other than the input and the output layer).


Machine Learning

Predicted the temperature of a given city and major greenhouse gases affecting it across a specific time period, using an ARIMA model for time series forecasting in Python


Global Temperature Change Prediction

Climate Change and its impact on health


Identified the AQI levels of different gases and analyzed the correlation between temperature, deaths, and pollution.



Performed sentiment classification using ensemble learning on tweets. 


Twitter Sentiment Analysis

Other Projects

A robotic arm which rotates and revolves around its axis to perform various functions where the programming was done in Python using Computer Vision


Selective Compliance Assembly Robotic Arm

Android Chatbot using


An android chatbot where is used for machine learning and firebase is used to store the data



This is the app for retrieval of data from firebase


Information Retrieval from Firebase

New York City
New York City

Elastic Cloud Infrastructure: Scaling and Automation

Google Cloud
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Essential Google Cloud Infrastructure: Foundation

Google Cloud
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Essential Google Cloud Infrastructure: Core Services

Google Cloud
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Machine Learning

Stanford University
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Big Data - Fundamentals

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GCP Fundamentals: Core Infrastructure

Google Cloud
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Reliable Google Cloud Infrastructure: Design and Process

Google Cloud
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Microsoft Azure Fundamentals

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Introduction to Software Product Management

University of Alberta
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Introduction to Corporate Finance

Wharton Online | The Wharton School
View Certificate

New York City