Project: Oil & Gas Plant Digital Twin | Digitization Project
• Collaborated with a team of 6 members to implement an optimization algorithm for a virtual plant, considering variables like raw material prices, temperature, pressure, and duration to assess real-world feasibility.
• Actively contributed as a key member in the development of the Python backend logic for a digital twin of an oil & gas plant, facilitating effective simulation and optimization processes alongside team members.
• Designed the architecture for the digitization application of the Oil and Gas plant, ensuring seamless integration with existing systems while gathering input from various stakeholders.

Project: Real-Time Optimization | Machine Learning
• Worked collaboratively within a team of 3 members to enhance optimization algorithm performance with multiprocessing, achieving a remarkable reduction in runtime by 90%.
• Partnered with data analysts to develop Python code that fetches data from multiple sources, generating comprehensive reports in MS Excel for informed decision-making.

Project: Yield Optimizer Project | Differential Evolution Algorithm | Machine Learning
• Engaged in team efforts with 3 members to train machine learning models that predict propylene and ethylene yield from actual plant data, contributing to knowledge sharing and best practices within the group.
• Utilized these models in a DE algorithm to maximize the ethylene and propylene yield for an oil & gas plant, collaborating closely with process engineers for practical insights.
• Developed APIs using Flask/FastAPI and deployed them using Docker containers, ensuring smooth deployment workflows with the DevOps team.
• Played a key role in developing the backend for an API to send data for a dashboard from the database, working alongside frontend developers to ensure a cohesive user experience.

• Collaborated closely with a team of 10 members from the marketing team on customer segmentation using a clustering model, enabling targeted marketing campaigns tailored to specific customer needs.
• Analyzed marketing data with Python and shared valuable insights with the marketing team to enhance campaign performance measurement.
• Worked alongside stakeholders to build performance measurement dashboards for marketing campaigns, providing a comprehensive analysis of the target audience.
• Contributed to the development of performance measurement dashboards to track and assess the effectiveness of marketing strategies.
• Developed the technical flow/architecture and code for complex marketing campaigns, utilizing Python and SQL to streamline processes.
• Drove process enhancements by applying automation techniques, minimizing data latency, and achieving seamless data integration within the team.
• Created a data pipeline to migrate data from GCP to the Teradata database using Python and BigQuery, ensuring efficient data handling and transfer.
• Engaged with business analysts to understand business processes, the flow of data within and between processes, and recommended process improvements for better data quality and effectiveness.

• Set up docker containers on Nvidia DGX server for training deep learning models and enable rapid analytics using GPUs
• Created a dashboard to monitor server and GPU statistics using NVDashboard and deployed using Docker
• Developed a Flask Application to manage ML models and provide an admin console for NVIDIA edge devices
• Developed Python scripts for converting raw data into KITTY Format for object detection algorithms
• Enabled rapid data analytics on huge datasets using Nvidia GPU by setting up docker containers on server
• Created visualizations using Tableau Desktop and Python libraries (Plotly, Seaborn, Matplotlib)
• Schedule python scripts on Linux Servers and devices (NVIDIA Jetson Devices, NVIDIA DGX Server)
• Used transfer learning to re-train and deploy pre-trained ML models from Nvidia AI for License Plate Recognition

Data Analysis

• Developed Python scripts for cleaning and formatting data received from inbound systems
• Developed monthly sales reports in Tableau Desktop

Application Development

• Collaborated with a team of 8 members from cross-functional teams to develop PLSQL procedures and functions for data processing tailored to project requirements, ensuring alignment with business objectives.
• Scheduled shell scripts using Crontab and managed Oracle Solaris Servers based on Linux, facilitating smooth and efficient operations within the team.
• Conducted performance tuning of database procedures and SQL queries using profiling tools and index rebuild techniques, leading to significant efficiency gains.
• Enhanced application performance through strategic index rebuilds, freeing up 18GB of space on the production server and contributing to overall system stability.
• Utilized SQL Loader to efficiently load data from flat files to Oracle tables, ensuring seamless data integration for project needs.
• Worked collaboratively to develop the front-end for an Oracle Data Migration web-based tool using HTML, CSS, and JavaScript, improving user experience and accessibility for stakeholders.

International Institute of Information Technology - Bangalore (IIIT-B)

Developed practical skills in data science through industry projects, mastering tools like Python, R, MySQL, and Tableau. Gained expertise in data manipulation, analytics, and machine learning under guidance from IIIT-B experts.

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College of Engineering Roorkee

Completed B.Tech in Electronics and Telecommunication, gaining hands-on experience in digital circuits, robotics, and technical projects while actively participating in coding challenges and cultural events.