A Data Scientist by Qualification, a Problem Solver by Mind and a Tech Enthusiast by Heart. Also, a die hard FC Barcelona fan.
Facilitating end-to-end ML projects in my role of Lead Data Scientist for the Return to Stock (RTS) project, right from establishing a proof-of-concept, to delivering and maintaining a Machine Learning model in production that predicts Return to stock prescriptions in CVS pharmacy stores.
Simultaneously contributing to two different projects apart from being the owner of the RTS project, which require a combination of software development and Machine learning skills to continuously develop and maintain them based upon business requirements.
Effectively maintain and develop communication with business partners to interpret model performance, analyze false positives and collaborate together to identify issues and resolve them through meticulously designed solutions.
Developed an ML Lifecycle tracking dashboard using MLflow to version iterated ML models, log model artifacts, monitor and track model performance metrics, all in one place for the leadership.
Contributed to an ongoing ML Project for a tech-based client, which required executing distributed queries on RDD's with PySpark and performing big data experimentation with Spark ML on Databricks.
Implemented custom NLP-tools such as Document Classifier, Named Entity Recognizer and Text Augmentation tool into the codebase of Rho AI's enterprise Machine Learning platform Sermos, by fine-tuning state of the art models such as Longformer, GPT-2, BERT, etc.
Experimented and analysed various Unsupervised Machine Learning approaches to build a similarity-based recommender system by clustering similar companies using key datapoints, for users searching for specific companies on CRANE's web platform.
Working on the Project - Improving observed and modeled air pollution data quality over sub-Saharan Africa using machine learning
The goal of the project is twofold: To better understand and further improve the use of low cost air pollution sensors and to analyze and characterize air pollution data in sub-Saharan Africa.
Graduate teaching assistant for MECEE 4520 - Data Science for Mechanical Systems by Dr. Josh Browne.
Primary responsibilities of mine involved grading assignments and projects that cover the syllabus of the course, and holding office hours to help students with foundational concepts of Data Science spanning from Probability Theory, Statistics, Programming and Machine Learning.
Graduate teaching assistant for COMS 4995 - Machine Learning for Financial Applications by Dr. German Creamer.
Instructing Students on foundational algorithms of supervised ML such as Naive Bayes, Regressions, Decision trees/ Random Forests, SVM's, HMM's, etc. Also responsible for grading and evaluating assignments designed on Quantopian.
Graduate teaching assistant for COMSE6998 - Fundamentals of Speech Recognition by Dr. Homayoon Beigi.
Primary responsibilities of mine involved grading assignments and projects that cover the syllabus of the course, holding office hours to help students with questions and doubts regarding the same.
Developed various sample python-projects such as Instagram Bot, Genre-based Song Classifier and Web-crawler which served as real-world examples of final deliverables for the course ’Introduction to Python Programming’, by Acadview.com (now acquired by upGrad.com).
GPA: 3.7/4
GPA: 8.96/10
Check the Colab File on Github
Check the Project Colab File on Github
Check Project Report