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Data Science with less than a year in retail reporting, ETL, and AI-based object detection.
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Data Analytics fresher with hands-on project experience in end-to-end retail reporting ETL pipelines, SQL querying, Power BI dashboard development, and KPI tracking across sales, category performance, basket size, and customer metrics. Certified Data Science professional (ExcelR, Bangalore) and published IEEE researcher with a methodical approach to data quality and strong eagerness to grow in a fast-paced analytics consulting environment.
SCMS School of Engineering and Technology
B.E. · Electronics & Communication Engineering
August 1, 2021 – June 30, 2025
ExcelR Solutions
Data Science Trainee (Internship in Training)
October 1, 2025 – March 1, 2026
Bengaluru, Karnataka, India
Retail KPI Intelligence Dashboard
January 1, 2026 – March 1, 2026
Simulated a 50,000-row multi-source retail dataset (POS sales, CRM, product catalogue) and built a full ETL pipeline in Python, cutting manual data-prep time by ~60%. Wrote 15+ SQL queries to extract weekly sales, category revenue, and basket-size metrics — catching and resolving 3 categories of data inconsistency before dashboard ingestion. Delivered a 5-page executive Power BI dashboard with DAX-driven KPI scorecards, YoY growth trends, and region/category drill-through mirroring LuLu Retail GCC reporting requirements. Implemented a data validation checklist (null handling, deduplication, format standardisation), achieving 100% reconciliation accuracy across all outputs.
View ProjectDeep Learning-Based Human Detection Rover
September 1, 2024 – March 1, 2025
Developed an AI-based real-time object detection system using YOLOv3 deployed on Raspberry Pi for autonomous human detection in disaster-zone environments. Designed a modular, object-oriented system architecture integrating GPS module, PIR sensor, and motor controller, ensuring reliable hardware-software interfacing. Built an SQL-based data pipeline to log detection events, GPS coordinates, and sensor triggers and generate automated alerts demonstrating structured data handling under real-time constraints. Research findings published and presented at IEEE ICSCC-2025, translating technical work into stakeholder-ready documentation.
IEEE Conference Publication – ICSCC-2025
IEEE Proceedings
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a blend of business intelligence (Retail KPI Dashboard) and cutting-edge AI/robotics (Human Detection Rover), indicating a diverse interest and ability to work across different problem domains. The internship in data science training aligns well with a growth-oriented culture. The publication at IEEE suggests a proactive and research-driven mindset, which can be a strong cultural asset. The target role of Data Science is well-aligned with the candidate's project experience and training.
Soft Skills & Operational Fit
The candidate demonstrates a methodical approach to data quality and a strong eagerness to grow, as evidenced by their detailed data validation checklist implementation and pursuit of a structured data science training program. Their ability to translate technical work into stakeholder-ready documentation (IEEE publication) suggests good communication and presentation skills. The project diversity indicates adaptability and a problem-solving mindset, which are valuable for operational fit.