Machine Learning Data Science

GAUTAM K BALGI

315-***-**** • ******@***.*** • www.linkedin.com/in/gautam-balgi/

EDUCATION

Syracuse University, School of Information Studies, Syracuse, NY August 2024 - May 2026 M.S. In Applied Data Science

Modules: Applied Machine Learning, Database Management Systems, Natural Language Processing Manipal University, Manipal Institute of Technology, Karnataka, India July 2019 - August 2023 B. Tech in Automobile (Minors in Fundamentals of Computing) Modules: Statistics, Probability, Linear Algebra, Calculus, C and Python, Essentials of Management TECHNICAL SKILLS

Programming Languages: C, C++, C#, Python, Java, MySQL, HTML, CSS, and JavaScript, R. Frameworks: Angular, ASP.net, Flask, and Entity framework. Libraries: TensorFlow, PyTorch, AutoML, Keras, Pandas, NumPy, Matplotlib, Plotly, NLTK, Scikit-learn. Others: Tableau, Jupyter Notebook, GitHub, MS PowerPoint, MS Excel, MS Word, Adobe Premiere pro, AWS, Azure. WORK EXPERIENCE

Graduate Student Researcher, NEXIS Student Technology Labs, Syracuse August 2024 - January 2025

• Examined sentiment in 50,000+ tweets about the 2024 USA election using Python, effectively reducing data noise by 30% and providing actionable insights for strategic decision making.

• Leveraged statistical modeling with Python (Matplotlib, Pandas) to uncover sentiment trends, increasing trend detection accuracy by 25% and highlighting key shifts in public opinion.

• Streamlined machine learning workflows using BERT models and NLP techniques like tokenization and sentiment analysis, elevating overall model accuracy to 85% and refining text classification efficiency. Data Analysis Intern, LTI Mindtree India, Remote, India January 2023 - December 2023

• Designed interactive dashboards with MySQL and Tableau in a dynamic 12-member team, significantly boosting data speed by 40% and enhancing data-driven decision-making processes.

• Implemented predictive models in Python, effectively employing linear regression with an impressive R-squared value of 0.6, successfully explaining 60% of the variance in forecasts.

• Transformed data reliability by 35% practicing techniques like missing value imputation and data transformation, ensuring cleaner datasets for more accurate analysis.

After Sales Intern, Mercedes Benz, Goa, India June 2022 - July 2022

• Performed comprehensive maintenance on over 50 vehicles, including oil changes, brake inspections, and tire rotations, to ensure optimal performance and extend vehicle longevity.

• Diagnosed and resolved issues in 45+ vehicles, with a primary focus on engines and electronic systems, enhancing overall functionality and reducing downtime by 25%.

• Addressed post-delivery concerns for 20+ customers, bolstering satisfaction and strengthening problem-solving skills. PROJECTS

South Carolina Energy and Weather Analysis: August 2024 - December 2024

• Assessed energy consumption data for 5,000 residential properties in R, concentrating on peak demand during July.

• Constructed machine learning models, including random forest and linear regression, to accurately predict hourly energy usage, improving demand forecasting precision by 25%.

• Evaluated hypothesis testing and correlation analysis, narrowing down 140+ factors to 42 key drivers of energy consumption. E-learning Database Management System: August 2024 - December 2024

• Engineered a robust e-learning database system using Azure Database and Power Apps, seamlessly integrating SQL queries and a Python based interactive application for streamlined and efficient data management processes.

• Generated dynamic Power BI visualizations to track real-time metrics such as user scores and activity trends, improving reporting efficiency by 30%.

• Enhanced system insights and analytics, enabling more informed decision making and improving user operations, resulting in a 20% increase in operational efficiency.

Movie Recommender System January 2023 - February 2023

• Developed to build a content-based movie recommender system website utilizing Python libraries such as NumPy and Pandas, showing five films based on user input.

• Optimized HTML and CSS to design a responsive interface, increasing user engagement by 30%.

• Customized Python and data manipulation techniques to optimize content generation and enhance recommendation accuracy.

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