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Data Analyst with less than a year in Data Analytics & ETL Pipelines
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Computer Science graduate with internship experience in data analytics, ETL pipelines, SQL querying, dashboard development, and business reporting. Skilled in Python, SQL, Power BI, Pandas, and data visualization with hands-on experience processing 25,000+ records, performing exploratory data analysis, and delivering actionable business insights. Strong foundation in statistics, data cleaning, KPI reporting, and analytical problem-solving.
PES Institute of Technology and Management, Shivamogga
Bachelor of Engineering · Computer Science
August 1, 2021 – June 30, 2025
Intelligence Software Corporation Pvt. Ltd
Data Science Intern
February 1, 2025 – May 1, 2025
India
Real-Time Retail Analytics Dashboard
June 1, 2026 – Present
Built end-to-end analytics data pipeline integrating multiple retail datasets. Performed ETL, feature engineering, and KPI computations. Developed interactive dashboards for sales analysis and ad-hoc reporting. Improved reporting efficiency by 40%.
View ProjectCustomer Behavior Analysis
June 1, 2026 – Present
Analyzed customer shopping behavior dataset using Python (Pandas, Matplotlib, Seaborn) and PostgreSQL to uncover purchasing patterns, top-performing categories, and customer segmentation insights. Built SQL queries for data aggregation, joins, and group-based filtering to extract time-series trends and regional performance metrics. Developed interactive Power BI dashboard with dynamic slicers, KPI cards, and visual trend analysis for ad-hoc reporting and stakeholder communication. Managed the end-to-end data pipeline, tracking data from raw data ingestion and cleaning through to final dashboard delivery.
Sales Prediction System
June 1, 2026 – Present
Performed data cleaning and feature engineering. Built predictive models for sales forecasting. Optimized workflows using Python and Pandas.
Retail Demand Forecasting & Inventory Intelligence Dashboard
June 1, 2026 – Present
Analyzed 73K+ retail inventory and sales records using Python and Power BI to identify demand patterns, revenue drivers, and inventory optimization opportunities. Built interactive dashboards featuring executive KPIs, revenue trends, category performance analysis, and inventory intelligence for business decision-making; presented insights to stakeholders via structured business reporting. Performed data cleaning, exploratory data analysis (EDA), and ad-hoc analysis using Pandas and Power BI.
Data Analytics with Python
NPTEL
June 1, 2026 – Present
Python 101 for Data Science
IBM
June 1, 2026 – Present
Introduction to Cyber Security
Cisco
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, covering retail analytics, sales prediction, customer behavior, and inventory forecasting, indicates a broad interest in applying data analysis across different business domains. The technologies used (Python, SQL, Power BI, Pandas, NumPy, Scikit-Learn) align well with a typical Data Analyst role. The internship experience and personal projects demonstrate initiative and a proactive approach to skill development, suggesting a good cultural fit for a growth-oriented environment. However, the candidate is still pursuing their bachelor's degree, which might indicate a need for mentorship and structured guidance.
Soft Skills & Operational Fit
The candidate demonstrates good operational fit through their project descriptions, which highlight end-to-end data pipeline management, collaboration with cross-functional teams, and communication of findings to stakeholders. Their experience in improving reporting efficiency and optimizing workflows suggests a results-oriented approach. However, the resume does not provide explicit details on soft skills like problem-solving methodologies, adaptability, or leadership, which would require further validation.