Building scalable data pipelines and ML infrastructure.
2 years of experience transforming raw data into actionable insights.
I'm a Data Engineering for AI graduate student based in France, passionate about building robust data infrastructure that powers intelligent systems. My journey in data started with curiosity about how companies turn chaos into clarity.
With 2 years of hands-on experience as a Data Analyst at Comcast, I've developed a deep appreciation for clean data architecture, efficient pipelines, and the art of making data accessible to those who need it most.
I thrive on solving complex problemsβwhether it's optimizing ETL workflows, designing data models, or experimenting with machine learning pipelines. I'm always looking for opportunities to learn, grow, and contribute to teams building impactful data solutions.
Identified potentially fraudulent healthcare providers by analyzing abnormal insurance claim patterns and generating a fraud risk score to support investigation and decision-making.
Built an end-to-end ETL pipeline that scrapes book data from a public website, cleans and validates it using Python, and stores it in a SQL database for analysis.
M.Sc. Data Engineering for AI
2024 - 2026 | France
Specializing in building scalable data systems for artificial intelligence and machine learning applications.
Great Lakes Institute of Management
2021 - 2022 | Chennai, India
Post Graduate Diploma in Management specializing in Data Science and Engineering with focus on analytics, machine learning, and business intelligence.
Loyola College
2018 - 2022 | Chennai, India
Foundational studies in computer science with focus on data structures, algorithms, and software engineering principles.
I'm currently looking for internship opportunities in Data Engineering across Europe. Feel free to reach out if you'd like to discuss potential collaborations or just say hello!