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Junior Data Analyst with less than a year in Python, SQL & Power BI
Results-oriented Computer Science undergraduate at Andhra Loyola Institute of Engineering and Technology with hands-on experience applying quantitative and statistical methodologies to real-world datasets. Proficient in end-to-end data pipeline development – from raw data ingestion and cleaning to feature engineering, exploratory data analysis (EDA), and insight visualization using Python, SQL, and Power BI. Demonstrates strong business acumen through translating complex analytical findings into actionable, stakeholder-ready narratives that drive informed decision-making. Passionate about leveraging data driven frameworks to uncover hidden patterns, optimize operational workflows, and deliver measurable business value in dynamic, cross-functional technology environments.
Andhra Loyola Institute of Engineering and Technology
Bachelor of Technology (B.Tech) · Computer Science & Engineering
August 1, 2022 – June 30, 2026
ZPHS School, Bhimavaram
Secondary School Certificate (SSC) · 10th Grade
June 1, 2020 – May 31, 2020
SAV & NVJR Junior College
Higher Secondary Certificate (HSC) · Science Stream
June 1, 2020 – May 31, 2022
Smart Traffic Light Control Using AI & Data Analytics
January 1, 2024 – June 1, 2026
Data Collection & Preprocessing: Collected and processed traffic surveillance data from multiple road intersections. Performed data cleaning, image preprocessing, vehicle count extraction, and handled missing or inconsistent records using Python and Pandas. Traffic Pattern Analysis: Analyzed historical traffic flow data to identify peak-hour congestion patterns, vehicle density trends, and average waiting times. Utilized SQL queries and statistical techniques to generate actionable traffic insights. AI-Based Signal Optimization: Developed an AI-driven traffic signal control system that dynamically adjusted signal timings based on real-time vehicle density and traffic conditions, reducing unnecessary waiting times and improving traffic movement efficiency.
Business Intelligence Sales Dashboard (Power BI)
January 1, 2023 – January 1, 2024
ETL Processing & Data Modeling: Designed and executed a full ETL pipeline - extracting raw transactional sales data from MySQL and Excel flat files, transforming it through Power Query (M Language) for deduplication, date standardization, and currency normalization, and loading it into a star-schema data model with dimension and fact tables optimized for analytical querying. Dashboard UI/UX & KPI Metric Design: Developed an interactive, multi-page Power BI dashboard featuring DAX-calculated KPIs including Month-over-Month Revenue Growth, Customer Lifetime Value (CLV), Product Return Rate, and Regional Sales Penetration; implemented drill-through filters, dynamic slicers, and conditional formatting heatmaps to deliver a self-service analytics experience. Stakeholder Decision Support: Enabled the business stakeholder persona to identify the top-3 underperforming product categories driving a 17% revenue shortfall in Q3, leading to a simulated inventory reallocation strategy that projected an 11% improvement in gross margin - demonstrating the direct link between data visualization and data-informed business decisions.
SQL for Data Science
UC Davis / Coursera
June 1, 2026 – Present
Google Data Analytics Professional Certificate
Google / Coursera
June 1, 2026 – Present
Python for Everybody Specialization
University of Michigan / Coursera
June 1, 2026 – Present
Power BI Desktop for Business Intelligence
Udemy / Maven Analytics
June 1, 2026 – Present
Machine Learning Crash Course
Google Developers
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a good diversity in application areas (traffic control, sales analytics), indicating adaptability and a broad interest in data-driven solutions. Active participation in technical project exhibitions and coding competitions suggests a proactive and engaged approach. The listed interests, such as exploring open-source data repositories and reading tech blogs, indicate a continuous learning mindset. However, the experience level is zero, which might require more mentorship and integration into a professional team culture.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, data storytelling, problem decomposition, and adaptability through project descriptions and listed soft skills. The ability to work with cross-functional teams is also mentioned. These align well with the collaborative and problem-solving nature of a data analyst role.