About
I enjoy working at the intersection of data engineering, machine learning and analytics — building pipelines, models and stories that help teams make better decisions.
Data Engineer & Machine Learning Enthusiast focused on building scalable data systems and translating data into business impact.
Background
My background spans cloud-native data pipelines on AWS and Snowflake, predictive modelling using Python and scikit-learn, and analytics storytelling with tools like Power BI and Tableau. I’ve supported financial and reporting teams with reliable data, while also experimenting with churn prediction and other ML use cases.
I like to work end-to-end: understanding the business problem, shaping the data model, designing the ETL/ELT flow, training and evaluating models, and then communicating the results clearly to stakeholders.
Education
Master of Analytics — RMIT University
Bachelor of Technology- Electrical and Electronics Engineering — APJ Abdul Kalam Technological University
Currently focused on
- Building an end-to-end Customer Churn Prediction project in Python.
- Strengthening ETL/ELT & Data Engineering patterns using AWS & Snowflake.
- Improving feature engineering & model tuning to lift predictive performance.
- Curating a clean, recruiter-friendly GitHub portfolio of real projects.