Atul Bhardwaj
Data Science Graduate Student | ML & Cloud Engineer | Building Scalable AI Solutions
Data Science Graduate Student | ML & Cloud Engineer | Building Scalable AI Solutions
Driven by data. Focused on impact.
I'm a Computer Science graduate student pursuing a Master's in Data Science at Seattle University, where I'm deepening my expertise in machine learning, statistical modeling, and cloud technologies. My focus is on building practical skills that bridge academic theory with real-world business applications.
I work across predictive modeling, data analytics, and cloud engineering. My projects include developing machine learning models for heart disease prediction and building solutions that reduced operational inefficiencies by 80%. I focus on solving real problems—improving patient care through clustering analysis and enhancing student services with data insights.
My technical expertise spans Python, SQL, AWS (EC2, S3, Lambda, EMR), TensorFlow, PyTorch, Scikit-learn, Apache Spark, Power BI, and Tableau. I build end-to-end data pipelines, develop machine learning models, and create analytics solutions that translate data into clear, actionable insights.
I'm looking for Data Science, AI Engineering, or Cloud roles where I can build scalable solutions that drive business results and create positive impact.
Tools and technologies I work with
Versatile coding expertise across multiple paradigms
Advanced ML frameworks and algorithms
Building and optimizing data pipelines
Transforming data into actionable insights
SQL and NoSQL data management systems
Scalable infrastructure and distributed computing
Core competencies in data-driven environments
Building impact through data-driven solutions
Statistics Without Borders
September 2025 - Present | Seattle, WA
Seattle University
June 2025 - Present | Seattle, WA
Seattle University
December 2024 - March 2025 | Seattle, WA
Ganga Institute of Technology & Management
November 2022 - May 2024 | India
Solving real-world problems with data and code
November 2025
Conversational AI chatbot for banking transactions with NLU capabilities.
In Progress
Full-stack application providing intelligent code refactoring suggestions.
Month Year
Project description goes here. Describe what the AI/ML model does, the techniques used, and the problem it solves (e.g., sentiment analysis, recommendation systems, etc.).
Nov 2025
Serverless data engineering pipeline analyzing 1,000+ trending videos across 5 regions with automated ETL workflows.
March 2025
Scalable distributed search engine on AWS infrastructure.
Month Year
Project description goes here. Describe the cloud services used, data pipelines, and architecture implemented.
September 2025
Unsupervised learning for campus operations optimization.
Month Year
Project description goes here. Describe statistical modeling, visualization, and actionable insights derived from the data.
Month Year
Project description goes here. Describe the data exploration, predictive modeling, and how insights drove business decisions.
Research contributions to the field
IEEE Xplore · 2024 | Read Paper →
Comprehensive evaluation of six supervised machine learning algorithms for predicting heart disease, focusing on precision, recall, and F1-score optimization to minimize false negatives in clinical decision support systems.
EAI Journal · 2024 | Read Paper →
Novel approach using Bidirectional LSTM with Convolution for identifying and classifying toxic comments in online platforms, demonstrating improved performance in natural language processing tasks.
Continuous learning and professional development
Let's connect and create something impactful together
