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Data Science with less than a year in Python, SQL & Power BI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI-enabled Data Analyst with a B. Tech in Computer Science, skilled in Python, SQL, Excel, Power BI. Experienced in end-to-end data analysis, including data cleaning, exploratory data analysis (EDA), SQL querying, and interactive dashboard development. Proficient in leveraging AI tools such as ChatGPT, GitHub Copilot to automate workflows, optimize queries and improve analytical efficiency. Passionate about transforming raw data into actionable insights to support business decision-making.
GIET Engineering College
Bachelor of Technology · Computer Science and Engineering
August 1, 2020 – June 30, 2024
Sales Performance Dashboard
June 24, 2026 – Present
Analyzed 10,000+ sales records using SQL to identify revenue trends, regional performance, and customer purchasing behavior. Built an interactive Power BI dashboard tracking KPIs such as revenue, profit margin, and month-over-month growth rate to support data-driven decision-making. Performed region-wise and product-wise segmentation analysis to identify top-performing and underperforming categories. Reduced manual reporting effort by 30% by automating dashboards, enabling faster business decision making.
Customer Churn Analysis
June 24, 2026 – Present
Analyzed 5,000+ customer records using SQL to extract churn-related patterns and segment customers based on purchasing behavior. Performed Exploratory Data Analysis (EDA) using Pandas to uncover key churn drivers such as tenure, purchase frequency, and spending decline. Developed a Logistic Regression model achieving 82% accuracy in predicting customer churn. Generated actionable insights to support retention strategies, with potential to reduce churn by 15-20%.
Supply Chain & Inventory Optimization Analysis
June 24, 2026 – Present
Analyzed 5000+ inventory and order records using SQL and Python to identify demand patterns, stock imbalances, and regional delivery delays. Developed and optimized SQL queries (JOINs, aggregations, window functions) to calculate key KPIs such as stock turnover ratio, inventory holding days, and stockout frequency. Segmented products into fast-slow and non-moving categories, identifying 30% overstocked inventory and opportunities to reduce holding costs. Built an interactive Power BI dashboard with KPI cards and filters to monitor inventory health, supplier performance, and order fulfillment efficiency.
Foundations: Data, Data, Everywhere
October 1, 2025 – Present
Introduction to Data Analyst
IBM
June 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data science skills to diverse business scenarios (supply chain, sales, customer churn). The use of AI tools like ChatGPT and GitHub Copilot indicates an openness to leveraging new technologies for efficiency. However, the lack of professional experience and a strong focus on academic projects might require a supportive environment for transitioning into a corporate data science culture.
Soft Skills & Operational Fit
The candidate highlights analytical thinking, problem-solving, communication, adaptability, and quick learning as soft skills. These are crucial for a data science role, indicating a potential for effective collaboration and continuous improvement. The project descriptions suggest an ability to translate business problems into data solutions and present insights clearly.