# Divyansh Chaudhary > SDE | Masters Computer Science @ UIUC Location: San Francisco Bay Area, United States Profile: https://flows.cv/divyansh Software Engineer (Backend) @ HabiTerre Research Assistant @ UIUC Research Assistant (Hourly) @ RailTEC ## Work Experience ### Software Engineer (Backend) @ HabiTerre Jan 2024 – Present | Illinois, United States Developed REST API infrastructure using AWS API Gateway and Lambda functions to automate client onboarding and project quota allocation, supporting scalable client management operations Wrote testing protocols with pytest framework, achieving 90% code coverage through integration and unit testing to validate API functionality, debugging and performance monitoring Developed CI/CD pipelines using Spinnaker and Jenkins with Docker containerization, automating lambda deployments and optimizing API concurrency for uptime and low latency Engineered end-to-end custom API endpoints with integrated business logic and documented customer-facing solutions for knowledge transfer ### Graduate Hourly @ RailTEC at Illinois Jan 2024 – Jan 2025 | United States Developed Python visualization and analysis scripts to process L-rail embedded sensor data, enabling comprehensive railroad infrastructure monitoring and performance assessment for research initiatives Built automated web scrapers and crawlers with multiprocessing Selenium pipelines, implementing bash scripts for routine data extraction and processing to streamline railroad data collection workflows ### Data Scientist @ Indian Institute of Technology, Ropar Jan 2022 – Jan 2023 | Rupnagar, Punjab, India Developed a machine learning classification model using Python to detect review bombing patterns by analyzing metadata and user reviews, successfully identifying fraudulent rating manipulations across entertainment platforms Engineered ETL pipelines to process large-scale datasets containing 45,000 movies, 26 million ratings, and 27,000 users, Incorporated knowledge graphs and critic reviews as control variables, leading to a 10% improvement in F1 score compared to the baseline model ### Data Analyst @ GUVI Geek Networks, IITM Research Park Jan 2021 – Jan 2021 | Delhi, India Automated the ETL process of student performance data gathered using RESTful API reducing processing time by about 50% Designed an interactive dashboard using Matplotlib, ggplot, Altair, and Plotly to visualize key performance indicators, resulting in an 80% increase in user clicks and engagement ### Data Scientist @ CogniTensor Jan 2021 – Jan 2021 | India Developed a predictive maintenance model using Random Forest to anticipate sensor failures, contributing to a 20% reduction in downtime and improved system reliability Collaboratively developed an Early Warning System leveraging machine learning techniques to detect fraudulent transactions, reducing false positives by 30% Applied Minority Over-sampling (SMOTE) to balance class distribution and used Self-Organizing Maps (SOM) for unsupervised clustering, building an anomaly detection pipeline with Python and scikit-learn that improved model robustness and detection accuracy Programmed Web Data Scrapers to extract data from official public sources, increasing the volume of collected data by 50% ### Machine Learning Engineer @ Internity Foundation Jan 2020 – Jan 2021 | Uttar Pradesh, India -> Gained practical experience in machine learning by working on a real-world project and applying various algorithms to large datasets. -> Conducted extensive data exploration and visualization to gain insights and understanding of the dataset, identifying key features and patterns. ->Performed data cleaning and preprocessing activities such as data imputation, feature scaling, and dimensionality reduction to improve the quality of the data and prepare it for analysis. -> Worked with various machine learning algorithms such as decision trees, random forests, logistic regression, and neural networks, to develop predictive models and evaluate their performance. -> Conducted feature engineering to identify and extract relevant features from the data, improving the accuracy of the models. -> Wrote blogs on Medium.com, sharing insights and techniques learned during the internship and showcasing expertise in machine learning. -> Published blogs were shared with big organizations, gaining exposure and recognition in the industry. ### Machine Learning Engineer @ TCS iON Jan 2020 – Jan 2020 | Ghaziabad, Uttar Pradesh, India -> Designed and developed a basic model for handwriting recognition using computer vision and machine learning algorithms. -> Built the model using Python and libraries such as OpenCV, Tensorflow, and Keras. -> Collected and preprocessed a large dataset of handwritten text to train the model, which included cleaning and normalizing the data to improve accuracy. -> Conducted experiments to fine-tune the model's hyperparameters and optimize its performance on test data. -> Evaluated the model's performance using metrics such as accuracy, precision, and recall, and iteratively improved the model based on the results. -> Implemented the model into an application for reading handwritten text and converting it to typed text, which was tested on a small dataset and achieved high accuracy. -> Collaborated with a team of peers to share knowledge and best practices and to ensure project deadlines were met. ## Education ### Master's degree in Computer Science University of Illinois Urbana-Champaign ### Bachelor of Technology - BTech in Computer Science Amity University ## Contact & Social - LinkedIn: https://linkedin.com/in/divyansh7c --- Source: https://flows.cv/divyansh JSON Resume: https://flows.cv/divyansh/resume.json Last updated: 2026-03-29