Professional Summary
Transforming complex data challenges into innovative business solutions
Certified Data Scientist with a Master of Arts in Economics from Bangalore University (CGPA 7.15) and certifications from IABAC (Grade A), NASSCOM (Gold), and DataMites. Specializing in transforming complex datasets into actionable business insights through machine learning, statistical analysis, and advanced analytics.
Completed a 6-month Data Science Consultant internship at Rubixe, working on POC projects and client assignments across data analysis, ML, and visualization. Creator of 2 PyPI-published Python packages — InsightfulPy (30+ EDA functions, 9 releases) and AutoCSV Profiler (automated CSV profiling with memory-efficient chunked processing) — reducing manual data analysis effort significantly.
Built 15 projects spanning ML pipelines (processing up to 58.4M records with 68.5% memory optimization), Python CLI tools, hybrid desktop applications (Electron + Python), and web development. Previously coordinated operations at Aditya Birla Fashion & Retail Ltd. (Pantaloons), recognized for dedicated and sincere conduct.
Key Achievements
Measurable impact through innovative data science solutions
Open Source Packages
Published 2 Python packages on PyPI — InsightfulPy (30+ functions, 9 releases) for exploratory data analysis and AutoCSV Profiler for automated CSV profiling with memory-efficient chunked processing.
ML Project Portfolio
Built 6 end-to-end ML projects across regression and classification — comparing 10+ algorithms per project, processing datasets from 200 to 58.4M records with up to 68.5% memory optimization.
Professional Certifications
Earned 3 professional certifications — IABAC Certified Data Scientist (Grade A), NASSCOM Certified Data Scientist (Gold), and DataMites training (120 hours) — plus 17 Kaggle micro-certificates.
Full-Stack Development
Delivered 15 projects spanning ML pipelines, Python CLI tools, hybrid desktop applications (Electron + Python), data extraction pipelines, and web applications.
Education Timeline
A summary of my academic journey and key milestones
Master of Arts in Economics
Bangalore University • CGPA 7.15 • Grade A (Very Good)
Specialized in Econometrics, Statistical Methods, and Research Methodology that form the backbone of my data science approach. Conducted Project on "Job Satisfaction & Work-Life Balance in Bangalore's IT Sector" analyzing survey data from 205 professionals using statistical techniques.
Relevant Coursework: Econometrics, Statistical Methods for Economists, Research Methodology, Mathematical Methods for Economists, Computer Applications for Economics Analysis, International Finance & Business, Economic Planning
Bachelor of Arts (History, Economics, Political Science)
Bangalore University • CGPA 7.36 • Grade A (First Class Distinction)
Strong foundation in economic theory, political analysis, and historical research under the CBCS scheme. Developed analytical thinking and quantitative reasoning through coursework in economics and banking & finance.
Key Areas: Economic Theory, Political Science, Banking & Finance, Entrepreneurship & Innovation, Data Interpretation, Statistical Methods
Professional Philosophy
Core values that drive my approach to data science
Continuous Learning
Self-taught transition from Economics to Data Science — earned 3 professional certifications, 17 Kaggle micro-certificates, and completed 152+ hours of structured training while building 15 real-world projects.
Analytical Rigor
Balancing theoretical understanding with practical application — structured ML pipelines with 10+ algorithm comparisons, statistical validation, cross-validation, and reusable modules built for reproducibility across projects.
Building & Sharing
Creating tools that solve real problems — from PyPI-published Python packages and ML pipelines to desktop applications and data extraction systems — and sharing them openly through MIT-licensed repositories on GitHub.
Certifications & Continuous Learning
Commitment to professional development and staying current with industry trends
Technical Skillset
Comprehensive expertise across tools, technologies, and methodologies for data science
Technical Tools
Development tools, frameworks, and platforms used for building data science solutions
Programming Languages
Data Science Libraries
Deep Learning Frameworks
Databases
Development Tools
Desktop & Runtime
Web Scraping & Automation
Testing & Code Quality
Technologies & Methodologies
Algorithms, methodologies, and technical approaches for data science and machine learning