About Me
Hi, my name is Ameya Karnad, and I am Software Engineer working at Google in Mountain View, California. I graduated from Columbia University with a Master’s Degree in Data Science in December 2019.
I am interested in the Applications of Data Science in the fields of computer science, technology, social sciences, public policy, political science and education. Recently, I have also worked Part-time as an Adjunct Associate Faculty at Columbia University
Experience
- Working for the Google Ads product in the Audience Management team
- Building a platform to help advertisers reach the right users across various advertising products
- Developing a robust framework for using first-party data as the advertising industry is moving towards a cookieless world.
- Working for the Oracle Transportation Management (OTM) Team at Oracle.
- Worked on the cross-functional teams across the product
- Currently Building Dashboards and Visualization components, as well as developing machine learning algorithms for the product
- Hired for the Course “Data Science Consulting” for two semesters.
- Directed and helped Students develop Data Science capstone Projects in a Consulting-based environment.
Edlab, Teachers College, Columbia University
https://edlab.tc.columbia.eduData Science Researcher
June 2019 - Dec 2019
- Worked on a Multi-platform recommendation system for various Teacher’s college library resources for enhancing Self Directed Learning (SDL)
- Own entire data pipeline and perform end to end data engineering
- Involves Development and research on Search and Recommendation systems, Social network analysis and Topic modelling
- Also worked on auto-tagging of documents and designed a python package for research metadata retrieval
- Technologies: Apache PredictionIO, MongoDB, EZProxy, Docker, Python, SQL
Columbia University
https://datascience.columbia.edu/students-recognized-excellence-during-reception-dsi-graduatesGraduate Teaching Assistant
Jan 2019 - May 2019
- Recieved Award for Excellence in Course Assistantship
- Teaching Assistant for the course “Applied Data Science”
- Course focuses on the practice of Data Science in the field of Educational Assessment, Health Care, Marketing, Advertising and Social Media
- Course deals with skills like Data analysis, Machine learning, Featuring Engineering and Interpreting & Communicating results.
- Responsibilities include evaluating assignments & projects and providing guidance to graduate students.
- Designed, tested and automated APIs for providing data analytics insights into software security compliance and risk data for a datacenter automation Software
- Implemented the software using python programing on kubernetes technology
- Won 2nd place in a site wide hackathon conducted by Hewlett Packard Enterprise by designing a ‘Docker and Kubernetes log monitoring Solution’
- Technologies: Kubernetes, Docker, Python
- Spin merged into Micro Focus in September 2017
Education
Columbia University, Data Science Institute
Master of Science - Data Science
2018 - 2019
B. V. B. College of Engineering and Technology (Visvesvaraya Technological University)
Bachelor of Engineering - Information Science and Engineering
2012 - 2016
Projects
A Bloomberg Sponsored Capstone Project to classify news articles
- Worked with unstructured news sources to build classifiers to identify editorial content for Bloomberg Terminal.
- Developed traditional classification algorithms with text based features like n-grams, Parts of speech, Named entities etc.
- Trained Natural Language Processing based Bidirectional LSTM, BERT, and XLNET Models for classification using Python.
- Languages: Python(Pytorch, TensorFlow, spacy), R(ggplot)
Educational Recommendation System
Recommendation system to recommend digital resources to students
- Developed a multi-platform database pipeline for physical and digital user behavior, and research content using AWS.
- Built and evaluated a hybrid recommendation system on multiple digital learning platforms
- Technologies: Python (nltk, predictionIO), SQL, MongoDB
A "Data Science and Public Policy" Project to Analyze Conflicts in Senegal
- Find correlation between factors such as Rainfall, Temperature, food prices and Bio-mass and Conflicts in Senegal
- Used Regression, SVM, Decision Trees and Time Series based models to predict Conflict. Link
- Built a reporting Dashboard that can be used by policymakers to take effective decisions to avoid natural resources shortages and conflicts.
Creating Insightful Visualizations on Airline Performance Data
- Performed Exploratory data analysis (EDA) and answered questions of interest on Airline On-Time Performance data for US
- Conducted the EDA using R’s tidyverse packages.
- Designed a Visualization tool in JavaScript and D3 to find flight delays between top airports.
- Tool Link
A Recommendation system for recommendation of Beer
- Built neighborhood based and model based collaborative filtering algorithms for beer recommendation
- Developed a Content based recommendation system using NLP on beer review-text
- Tackled recommendation concerns such as cold- start, variety, serendipity and accuracy
- Developed the project in python using surprise, NL toolkit and scikit-learn packages
Projects in Data Science and Public Policy
Mini Data Science Projects in Public Policy Context
Research Project in Educational Analytics
Evaluation and Validation of Problem Solving and Thinking Skills based on Student Academic Performance
- Implemented a modified K-means clustering algorithm on a Weighted Skill Score (WSS) to evaluate Problem solving and thinking skills of a student based on academic performance
- Analysis was done using R Programing
- Presented and published at IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) 2017, Link