Hello World

I am Utkarsh Chouhan,
a Data Science
enthusiast & a DevOps
engineer based
in New Delhi, India.

About

Recent Computer Science graduate with a strong foundation in DevOps, cloud technologies, and full-stack web development. Experienced in designing and deploying scalable, high-performance applications using modern tools. Passionate about research around emerging technologies. Seeking to enhance technical expertise and drive innovation through a Master’s program in Computer Science.

Download CV

Expertise

Python and Golang
DevOps
Data Science
Linux and Scripting
Web Development
Wordpress Development

Experience

Technologies Used: Python, pandas, scikit-learn, SQL, Apache Airflow, Tableau
Developed and deployed a predictive model to forecast customer churn, achieving a 92% accuracy.
Built and optimized data pipelines for ETL processes using Apache Airflow, reducing data processing time by 15%.
Created interactive dashboards in Tableau, presenting key metrics and insights to senior management.

Developed and deployed a sentiment analysis tool using AWS Sagemaker, AWS Lambda and Amazon Comprehend to analyze customer feedback data.
Managed data storage, security, and access control using AWS IAM policies and S3 bucket encryption for sensitive datasets.
Monitored AI model performance with Amazon CloudWatch and implemented automated scaling to ensure optimal performance under varying workloads.

Education

CGPA : 8.29, Credits Earned : 160

Learned the German Language from A1 till B2 Level.

Physics, Chemistry and Mathematics Major

Publications

Optimizing Cloud-Based E-Learning Platforms: A Comparative Analysis of Server-Based and Serverless Deployment Strategies

2024 IEEE I2CT

Conducted comprehensive research comparing cloud-based e-learning platforms focusing on deployment and performance optimization techniques.
Evaluated cost, scalability, performance, and customization of LMS platforms.
Applied cost-effectiveness models, case studies, and quantitative performance metrics to assess platform efficiency.
Analyzed server-based versus serverless cloud deployment models to determine the optimal solution.

View - IEEE Xplore

Comparing Microservices and Monolithic Applications in a DevOps Context

2023 IEEE ASIANCON

Researched the integration of DevOps and microservices to enhance application development agility and efficiency.
Analyzed the advantages of microservices over traditional monolithic architectures for large-scale applications.
Identified best practices for implementing DevOps and microservices strategies in organizations.
Provided insights on optimizing application growth and maintainability through modern development practices.

View - IEEE Xplore