Teaching Assistant

Course: Principles of Machine Learning

Indiana University Bloomington

• Supported Professor in teaching key machine learning concepts including supervised and unsupervised learning, regression, classification, clustering, neural networks, and model evaluation.

• Assisted around 90 students with assignments and projects focused on implementing machine learning algorithms in Python, reinforcing theoretical course material.

Data Scientist

Omdena

• Performed data collection by crawling 25,000+ job descriptions from diverse industries and regions to create a robust dataset for training machine learning models to detect gender and racial bias.

• Developed LSTM, BERT, DistilBERT, and RoBERTa models and evaluated their performance in accurately classifying biased versus neutral language in job postings.

Research Assistant

Indiana University Bloomington

• Developed interactive Tableau dashboards for Grants Map, facilitating detailed exploration of foundation funding, and created activity area-based visualizations for insights on top foundations and donation patterns.

• Contributed to network analysis by identifying anomalies, creating Jupyter Notebooks for consistent analysis, and summarizing relevant network econometrics papers for future research.

Software Developer

Tata Consultancy Services, India

Programmed an internal web application for a healthcare client using Springboot. Explored and implemented various attributes and data preparedness strategies crucial for Mainframe to Cloud migration.

Data Science Intern

Cluzters.ai, India

• Achieved exposure towards recommendation systems by applying appropriate custom-designed filtering models based on content-based, collaborative, and knowledge-based recommendation techniques.

• Conducted in-depth Data Science research and generated insightful content for cluzters.ai, gaining profound insights into the operations of a community-driven platform.

Data Science Intern

Bennett University, India

• Worked on a 25,331 image dataset, and utilised keras data augmentation techniques to address a set of 8 imbalanced classes.

• Conducted experiments with 5 machine learning models, by hyper-parameter tuning utilizing NVIDIA DGX.

• Published a research paper: ”Skin lesion analysis towards melanoma detection with deep neural networks.”