Headline

BTech Computer Science (Hons) Data Science with Minor in Economics | Aspiring Data Scientist | EDA • Data Visualization • ML & DL

About

I'm a Data Science graduate (B.Tech, Hons., Computer Science – Data Science, Minor in Economics) who likes building things end-to-end — from raw, messy data to a working model or dashboard someone can actually use. Over the past few years, I've worked across a wide range of problems: predicting disease risk from clinical data, classifying real vs. AI-generated images, building a generative AI pipeline that creates emotion-matched art, running sentiment analysis on stock market tweets, and prototyping a reinforcement learning agent for dynamic pricing. I've also spent time cleaning messy datasets, building BI dashboards, and translating findings for non-technical stakeholders. This range came from three internships (healthcare analytics at Cytecare Hospitals, backend/AI systems at Skyvion Technologies, and BI tooling at GoCrackIt) plus a coursework-heavy program that pushed me into ML, deep learning, NLP, computer vision, and IoT. I'm most interested in roles where I can keep working across the full pipeline — data, modeling, and communicating insights — rather than staying in just one lane. Currently exploring opportunities in Data Science, Analytics, and ML/AI roles.

Location

Bengaluru

AI stack

github copilot

langgraph

notion

openai

CrewAI

Microsoft Copilot

Work experience

AI Software Engineer Intern at Skyvion Technologies, Jan 2026 - Jun 2026 · 6 mos, Bengaluru, Karnataka, India, Contributed to a Smart Available-to-Promise (ATP) engine that combined supplier performance metrics with external time-series data (weather, holidays, news) for predictive risk analysis — hands-on experience integrating and modelling multi-source data for forecasting. Built and integrated backend modules using Python, Flask, and REST APIs, enabling modular workflows and document-level traceability across an AI-assisted ERP Supply Chain Management platform. Ran experiments and evaluated approaches under guidance to improve predictive risk scoring, documenting findings for the team. Worked in an Agile environment using Git, GitHub, and Postman to deliver scalable, production-oriented solutions.

AI/ML Intern at GoCrackIt, May 2025 - Jul 2025 · 3 mos, Bengaluru, Karnataka, India, - Led a comparative evaluation of Tableau, Power BI, Looker Studio, and Apache Superset, contributing to the adoption of Superset for automated analytics dashboards. - Designed and built interactive dashboards, reducing manual reporting effort through workflow automation. - Integrated REST APIs to enable real-time data ingestion and dynamic visualizations. - Collaborated with developers and designers to make dashboards more practical and user-friendly.

AI Intern at Cytecare Hospitals, Jun 2024 - Jul 2024 · 2 mos, Bengaluru, Karnataka, India, Analyzed clinical and patient-level datasets using Python and R, performing exploratory data analysis and data cleaning to surface actionable insights for hospital stakeholders. Developed interactive dashboards in Tableau and Power BI to visualize operational and patient trends. Built a Streamlit + OCR-based prototype to structure unstructured, handwritten data into a clean, analyzable digital format. Collaborated with clinical stakeholders to translate business requirements into technical, data-driven solutions.

Education

BTech in Computer Science (Hons) Data Science with Minor in Economics, Vidyashilp University

B.Tech (Hons.), Computer Science, Vidyashilp University