Instructor2020 - PRESENTColumbia University
Technologies: Natural Language Processing (NLP), Python, Deep Learning, Machine Learning, Hypothesis Testing, Front-end Development, Databases, Statistics, Programming
- Instructed graduate students in programming, statistics, databases, front-end development, business intelligence tools, hypothesis testing, machine learning, and other analytical skills.
- Led and established a collaborative culture where each member of our four-person instructional staff is fully committed to the success of each student.
- Consistently achieved high student satisfaction scores (4.5+/5).
Artificial Intelligence Researcher2020 - 2020Insight Data Science
Technologies: Amazon Web Services (AWS), Python, PyTorch, Scikit-learn, Word Embedding, Neural Networks, Learning to Rank, Natural Language Processing (NLP), Deep Learning, Model Tuning, Model Optimization, Machine Learning Model
- Built an intelligent search product for textbooks that uses ALBERT, a lightweight deep learning model, to translate students' search queries into results 100x faster than traditional table-of-contents methods. I was the sole developer.
- Served the model and information retriever by building a containerized web app (textbookqa.com) in Docker and AWS.
- Delivered an MVP within the four-week deadline and presented the product to stakeholders.
Data Scientist (Capstone)2019 - 2020Dotin
Technologies: LSTM, Python, PyTorch, Classification, Neural Networks, Model Optimization, Machine Learning Model, Data Science Consultation
- Predicted the validity of paid surveys with an accuracy of around 76% by building a long short-term memory (LSTM)-based architecture to use survey recipients’ mouse movements to help identify and recoup unjust survey costs.
- Achieved a peer-reviewed publication for our team’s research on validating survey responses (arxiv.org/abs/2006.14054). Commercialization of the survey validation product is in progress.
- Worked within an Agile framework in a team of eight.
Machine Learning Intern2019 - 2019Infosys
Technologies: Transformers, Python, NLTK, PyTorch, Word Embedding, Classification, Neural Networks, Natural Language Generation, Natural Language Processing (NLP), Deep Learning, Machine Learning Model
- Integrated a state-of-the-art NLP model (RoBERTa) with Stanford’s slicing functionalities to achieve top results on Stanford’s SuperGLUE, a leading NLP benchmark for evaluating general natural language understanding models.
- Placed as the first runner up out of 32 teams in the Annual InStep Hackathon, personalizing the user’s learning journey by implementing an innovative sequential recommender system for educational content.
- Detected fraudulent healthcare providers with an accuracy of 95% and recall of 90% by implementing a neural network architecture (PyTorch), outperforming the firm’s existing rule-based classifier by around 46%.
Data Science Intern2018 - 2019Byteflow Dynamics
Technologies: NLTK, PyTorch, Neural Networks, Data Science Consultation, Regex, Python, Machine Learning Model
- Built machine learning models to use news with time-series data to classify future stock price performance with 61% accuracy.
- Developed a Python crawler to extract around 5,500 financial news articles on a weekly basis for 100 tickers.
- Performed sentiment analysis of stocks by cleaning raw data using Regex and utilizing rule-based financial lexicons.
Co-founder | Vice President2016 - 2018Ummid A Hope Foundation
Technologies: Nonprofit, Business Management
- Raised $75,000+ to benefit abandoned girls in Udaipur, India, helping to build the core team and a global network of 1,000+ donors.
- Coordinated team meetings and the team technology stack to facilitate the organization's global outreach.
- Organized several local fundraising events to retain existing donors and attract new ones.
Business Analyst2014 - 2018Zodiac21 Solutions
Technologies: Tableau, Microsoft Excel, SQL
- Managed datasets with SQL, Excel, and Tableau to track KPIs, present dashboards, and discover actionable insights.
- Increased the average customer retention rate from 35% to 64% by leading a cross-functional, five-member team to develop web and kiosk applications for instantaneous customer-to-staff feedback.
- Implemented and trained 50+ staff members in using the latest tools for automation to enable digital reporting, cloud-based time tracking, and task management.