Hello, I'm
Amogh Ramagiri
Passionate about transforming data into insights and building innovative solutions that make a difference.
Amogh Ramagiri
Data Scientist Intern
@ Fulton Bank
📍Arlington, VA
Technical Skills
Languages:
Python
R
SQL
C
Data Analysis:
Pandas
NumPy
Scikit-learn
TensorFlow
Power BI
Tools:
Git
MySQL
MongoDB
AWS
Firebase
Supabase
About me
I'm a data enthusiast and problem solver with a strong interest in applying data science to the finance and banking industry. Currently, I'm working as a Data Scientist Intern at Fulton Bank, where I focus on creating dashboards, building reports, and developing KPIs that help teams make smarter business decisions.
Day to day, I work with SQL and Python to handle large datasets, perform data analysis, and engineer meaningful features that bring clarity to complex problems. I enjoy turning raw data into stories that people can act on — whether it's identifying trends, improving processes, or supporting strategic goals.
With a background in computer science and experience across India, Taiwan, and the U.S., I bring a well-rounded, global perspective to my work. I'm passionate about making data useful, understandable, and impactful.
Competencies:
- Python Programming
- Data Analysis
- Machine Learning
- Natural Language Processing
- Web Development
Experience
Education
Master of Science in Data Science
Aug 2024 - Present
The George Washington University, DC
Currently in my third semester studying NLP for Data Science, Cloud Computing, and Ethics for Data Science
Bachelor of Technology
Sept, 2020 - May, 2024
Presidency University, Bangalore, India
Pursued B.Tech in Computer Science and Engineering (Specialized in Artificial Intelligence and Machine Learning)
Publications
Image Classification for Optimized Prediction of Leukemia Cancer Cells using Machine Learning and Deep Learning Techniques
2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), 2023
Artificial Intelligence in Space-Limitations and its Solutions to Interplanetary CubeSats
2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), 2023
Intelligent Traffic Monitoring, Prioritizing and Controlling Model based on GPS
2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), 2023
Organizations
Institute of Electrical and Electronics Engineers (IEEE)
Student Member
April 2025 - Present
Active member contributing to research and development in electrical engineering, computer science, and related fields.
Data Science for Sustainable Development (DSSD)
Head of Data Science Research Team
Oct 2024 - Present
Leading the Data Science Research Team, spearheading sustainable development initiatives through advanced data science applications and research in energy efficiency and environmental impact analysis.
Professional Experience
Fulton Bank
Data Scientist Intern
May 2025 - Present | East Petersburg, PA
- Developed forecasting models for the internal Credit Risk team to predict interest rates and loan approval rates, enabling data-driven decisions while maintaining a low delinquency rate.
- Collaborated with the Lending and Risk teams to perform data profiling and mining using SQL, Python, and SSAS, improving data quality for credit risk analytics across business lines.
- Contributed to a large-scale data modernization project by migrating on-premises data infrastructure to Azure cloud, resulting in 43% improvement in system performance and 50%+ reduction in downtime.
- Rebuilt and optimized 15+ Power BI dashboards for key business lines using Microsoft Fabric and MS Power BI Azure, enabling real-time, cloud-native reporting and enhanced decision-making capabilities.
Data Science for Sustainable Development
Data Scientist Consultant
Oct 2024 - Present | Washington DC
- Designed strategy to reduce overall energy waste across 10 university buildings by 16%+ annually. Researched energy consumption patterns using Random Forest algorithm to identify peak usage times.
- Analyzed energy benchmarking data from 50+ university buildings, identifying critical factors impacting resource efficiency and sustainability trends to guide further research initiatives.
- Crafted a user-friendly interface in an interactive app hosted on the Streamlit Community Cloud; this resource facilitated real-time exploration of energy metrics across university buildings with enhanced latency.
Factocart, Velabh Technologies Pvt. Ltd.
Data Scientist
Mar 2024 - Aug 2024 | Bangalore, India
- Enabled strategic decisions about client acquisition and sales that drove 11% boost in overall sales within 6 months by analyzing 10GB+ datasets fetched from AWS RDS.
- Predicted customer demand with 92% accuracy, leading to 13% reduction in stockouts and optimizing inventory management across 10+ product categories using machine learning models.
- Performed hypothesis and A/B testing to evaluate the effectiveness of marketing campaigns, identifying high-performing strategies that led to a 15% increase in conversion rates.
- Created 20 detailed analytics reports using Power BI that provided actionable insights for decision-making; this initiative enhanced data visibility and led to a more efficient sales strategy implementation.
National Changhua University of Education
Research Assistant
Sept 2023 - Mar 2024 | Changhua, Taiwan
- Implemented dual-layer biometric authentication system integrating DeepFace for facial recognition and MFCC features for voice recognition, enhancing overall accuracy by 30% over traditional single-modal systems.
- Analyzed biometric authentication performance across diverse datasets, leveraging statistical techniques to validate system reliability and effectiveness.
- Architected an interactive solution via Flask and Python to access 1,200+ individual authentication records stored within NAS servers linked to Raspberry Pi units; attained meaningful gains in speed without sacrificing accuracy.
Projects
Student Performance Indicator – AWS Cloud
Built an ML pipeline to predict student performance using academic and socio-economic data, achieving 87% accuracy. Automated deployment via AWS CodePipeline and Elastic Beanstalk, reducing manual effort by 80%.
Energy Management System
Developed an interactive Streamlit app for analyzing university building energy data with ML models. Implemented Random Forest algorithms to identify consumption patterns.
Biometric Authentication System
Engineered dual-layer authentication system integrating DeepFace for facial recognition and MFCC features for voice recognition with 30% improved accuracy.
Credit Card Fraud Detection
Developed a credit card fraud detection model using supervised ML and ensemble methods (Logistic Regression, SVM, Random Forest, Bagging, Boosting). Achieved high accuracy with real-world data, minimizing false positives and boosting financial security.
NYC Taxi Fare Prediction
Built a regression model to predict NYC taxi fares using features like pickup/dropoff coordinates, time, and passenger count. Applied EDA, feature engineering, and trained models with hyperparameter tuning to improve accuracy on real-world fare data.
Car Price Prediction
Developed a machine learning model to predict car prices using features like year, mileage, and brand. Performed EDA, preprocessing, and trained models including Random Forest with hyperparameter tuning via RandomizedSearchCV to optimize performance.
Fashion MNIST Classification
Built a CNN using TensorFlow to classify the Fashion-MNIST dataset from Zalando Research. Trained on 60k grayscale 28x28 images, tested on 10k (80:20 split), classifying into 10 fashion categories (e.g., T-shirt, Sneaker, Bag). Achieved efficient image recognition.
Get In Touch
I'm always open to discussing new opportunities, interesting projects, or just having a conversation about data science and technology. Feel free to reach out!