Rahul Chauhan is an MS in Data Science student with strong programming skills and experience in machine learning, data analysis, and visualization. He has worked on various projects, including NLP research, predictive modeling, and dashboard creation, achieving high accuracy in predicting outcomes. His work experience includes functional consulting and data science roles, where he improved operational efficiency and developed data-driven solutions.

1. RAHUL CHAUHAN
720-755-4224 • rach3246@colorado.edu • LinkedIn • GitHub
EDUCATION
MS in Data Science 3.83/4.00
University of Colorado Boulder, CO, USA 08/22 – 05/24
B. Tech in Information Technology 8.39/10.00
University of Mumbai, MH, IND 08/17 – 05/21
SKILLS
Programming & Databases: Python, R, C#, SAS, SQL (MySQL, PostgreSQL, Cassandra DataStax)
Data Science & Machine Learning: Statistical Analysis, Machine Learning (SVM, Isolation Forests, Decision Trees), Neural
Networks (LSTM, GRU, CNN, ANN), NLP (NLTK, VADER, Word2Vec), Predictive Modeling, Time Series Analysis, Data
Manipulation (Pandas, NumPy), Big Data (Hadoop, Spark, Kafka), MLOps (CI/CD, model monitoring)
Visualization & Platforms: Power BI, Tableau, Excel, SAP, Kubernetes, Docker, OpenShift V2
RESEARCH EXPERIENCE
Graduate Research Assistant
Leeds School of Business, University of Colorado at Boulder, CO, USA 01/24 – 05/24
• Utilized NLP techniques (Word2Vec, VADER, LDA) to analyze 500+ comments on corporate gun violence stances, achieving
80.67% prediction accuracy
• Automated the collection and literature review from 1,500 market research papers using document parsing algorithms, reducing
manual effort by 90% and accelerating the research process by 35%
Data Scientist (Remote) [Medium Article]
99P labs, Honda Research Institute, CA, USA 01/24 – 05/24
• Architected a data pipeline for a telematics dataset of over 1M+ rows, developing driver profiling and behavior scoring systems
with Isolation Forest, XGBoost and ANN, yielding a prediction accuracy of 72.39%
• Designed a Power BI Dashboard for vehicle mobility management, visualizing fuel efficiency, cabin comfort, and speed
management to aid decision-making by 20%
WORK EXPERIENCE
Functional Consultant
LTIMindtree (Formerly known as Larsen & Toubro Infotech), MH, IN 07/21 – 07/22
• Leveraged SAP’s Plant Maintenance to conduct data-driven analysis, identifying trends and predicting maintenance needs, which
reduced equipment downtime and increased production efficiency by 12%
• Led the OneSAP system integration for Legacy Systems, using data analytics to streamline project management processes, assess
risks, and enhance decision-making, resulting in a successful transformation with a 40,000 euros turnover increase
PERSONAL PROJECTS
Insights on Delta Airlines using Machine Learning | RStudio | [Website Link]
• Extracted and analyzed over 20,000 Delta Airlines customer reviews from the Skytrax website. Employed data cleaning, EDA,
and various modeling techniques, improving prediction accuracy of customer sentiments by 11.52%
• Deployed machine learning models (Clustering, ARM, SVM, Regression, NB) to predict customer recommendations for Delta
Airlines, achieving the highest accuracy of 71.52% and identifying a 20% recommendation rate with an average rating of 3/5
Multivariate Time Series Analysis for Temperature Forecasting | Python | [Github Link]
• Engineered an LSTM-based neural network using TensorFlow, with an input layout of 7-time steps and 6 features. Achieved
training RMSE of 0.0279 and validation RMSE of 0.0296, reflecting high predictive accuracy
• Developed and implemented a deep learning model for temperature forecasting, including a 64-unit LSTM layer and two dense
layers for output processing, leading to the lowest RMSE scores observed in training and validation
Credit Card Transactions Grievance Dashboard | Tableau | [Tableau Link]
• Designed a Credit Card Fraud Complaints Dashboard using Tableau, enabling real-time tracking of 86,893 total grievances, and
significantly improving response times for effective and efficient fraud management strategies
• Created visual analytics with a “Weekly Trend” line graph and geographical data representation, enabling strategic decision-
making based on real-time grievance data and trends
OCD Patient Data Analytics and Visualization | SQL | [Github Link]
• Crafted a Health Analytics Dashboard using SQL and Excel, analyzing OCD diagnosis data for over 1,300 patients, thereby
enhancing strategic decisions based on detailed gender and ethnicity insights
• Streamlined monthly OCD diagnosis reporting through advanced SQL techniques, enabling efficient visualization in Power BI
and Excel, reducing manual data handling by 50%
Power BI-Driven Inventory Management Dashboard | Power BI | [Github Link]
• Established and implemented an Inventory Management Dashboard, optimizing data analysis and decision-making, achieving a
5.41 turnover ratio while managing a stock value of $77.3M across 303 SKUs
• Enhanced inventory management by visualizing data with bar graphs and pie charts, improving efficiency and accuracy