Chandan Rudrappa | Data Scientist

Hi, I'm Chandan Rudrappa.

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Self-driven and detail-oriented data scientist with a strong analytical mindset, passionate about building scalable ML solutions and solving complex real-world problems through data.

About

Data Science graduate from The University of Texas at Arlington. I enjoy turning messy data into clear insights and building end-to-end solutions that create measurable impact. I have hands-on experience with Python, PyTorch, TensorFlow, Streamlit, Flask, SQL, and big-data tools like Spark and Hadoop. My industry and research work spans NLP (TextCNN, Transformers), predictive modeling, dashboard development, and data automation. I’m committed to building scalable, meaningful applications—whether that’s a high-accuracy ML model, an automated analytics tool, or a streamlined data workflow.

Experience

UTA Social Work

Research Assistant

Developed a Streamlit application that ingests waiver documents in Excel format and automatically highlights content discrepancies, reducing manual review time by 50% and improving validation accuracy.
Built and deployed TextCNN and Transformer-based classifiers to categorize document context into 20+ tag categories significantly speeding up downstream document processing.
Tools: Python, Streamlit, Tensorflow, Keras, Huggingface Transformers, Pandas, NumPy

July 2025 - Present | Arlington, TX

UTA Mathematics

Graduate Math Tutor - Statistics

Tutored 100+ undergraduate students in Statistics, Probability, and Calculus I–III across two tutoring centers, improving student performance by an average of 20%.
Supported service-learning data projects with community partners, providing analytical and technical assistance to teams of 10–15 students.
Cleaned, transformed, and validated real-world community datasets, increasing data usability and enabling students to perform meaningful statistical analyses.
Guided students on research methodology, hypothesis testing, and statistical interpretation, helping translate community-driven questions into actionable insights.
Tools: Python, Excel, R

Jan 2025 - May 2025 | Arlington, TX

Analyttica Datalab Pvt. Ltd.

Data Scientist

Designed and developed 150+ reusable data science functions for the LEAPS analytics platform, enabling faster implementation of data visualization, data management, and time series analysis workflows.
Upgraded 80+ static matplotlib visualizations into interactive Plotly dashboards, increasing user engagement and reducing dashboard creation time by 25%.
Involved in building a recommendation engine to enhance the LEAPS user journey by providing personalized data science problem suggestions, improving platform retention by 15%.
Developed an internal employee management portal using Flask and Django, automating record tracking and improving data accessibility across teams
Authored 60+ Jupyter notebooks for applied data science case studies, helping users learn key ML concepts through hands-on experimentation.
Collaborated with cross-functional teams to create 5 instructional data science courses, simplifying complex topics and improving learner comprehension scores by 30%.
Led client open house sessions for Siemens and Aditya Birla Group, presenting classification and regression analyses to groups of up to 30 participants, strengthening client engagement and understanding.
Tools: Python, Scikit-learn, Pandas, NumPy, Matplotlib, Plotly, Jupyter

May 2022 - July 2023 | Bengaluru, India

Projects

                
                  Waiver Document Checker
                  
                  A Streamlit app that automatically compares waiver documents and highlights content discrepancies.
                
                  Accomplishments
                Built a Streamlit application that ingests Excel waiver files and highlights differences between versions.
Reduced manual review time by 50% through automated document comparison and structured output.
Integrated preprocessing and formatting pipelines to ensure consistent validation across diverse document types.

Scot Forge Data Analysis
                  Predictive modeling project on tensile test outcomes using industrial manufacturing data.
                
Accomplishments
                  Selected from 40+ teams to work directly with Scot Forge engineers on a real-world dataset.
Performed EDA, hypothesis testing, feature engineering, and preprocessing.
Built a classification model achieving 98.82% accuracy after resampling.
Identified key predictors influencing tempering effects on tensile strength.

Rover Vision System
                  Computer vision integration for autonomous rover navigation and object detection.
                
                Accomplishments
                  
                Implemented ArUco marker tracking and LiDAR-based object detection modules.
Integrated ZED stereo camera SDK for depth-based localization.
Configured and optimized the NVIDIA Jetson TX2 using the latest JetPack SDK.

Document Tag Classifier
                  NLP models to classify waiver content into 20+ tag categories using deep learning.
                
                Accomplishments
                  
                Developed TextCNN and Transformer-based classifiers for context tagging.
Improved tagging efficiency and reduced manual processing time significantly.
Enabled structured downstream automation for document review pipelines.

                  IMDb Top 250 Ratings Analysis
                  
                  Statistical analysis of IMDb’s Top 250 movie ratings using a Goodness-of-Fit test.
                
                  Accomplishments
                  
                Scraped IMDb Top 250 movie ratings using BeautifulSoup.
Performed exploratory analysis and applied a Goodness-of-Fit test to evaluate rating distribution.
Summarized findings and statistical insights in a structured analytical report.

                  SQL Tkinter Database App
                
                  A GUI-based application for managing and updating database records using Python and SQLite.
                
                  Accomplishments
                Developed a full GUI in Tkinter for interacting with an SQLite database.
Implemented CRUD operations and real-time data updates through the interface.
Built a clean and functional UI for user-friendly database navigation.