Junior Data Analyst with hands-on experience in SQL, Power BI, Excel, and Python, specializing in data cleaning, visualization, and business reporting. Built HR analytics dashboards and AI-assisted complaint classificati…
Junior Data Analyst with hands-on experience in SQL, Power BI, Excel, and Python, specializing in data cleaning, visualization, and business reporting. Built HR analytics dashboards and AI-assisted complaint classification systems delivering measurable operational improvements. Strong foundation in transforming raw data into actionable insights and supporting data-driven decision-making.
Built end-to-end analytics and ML projects including Credit Card Fraud Detection and HR Analytics Dashboard.Cleaned, processed, and analyzed 1K+ HR records using Excel and SQL Server to identify attrition trends and salary gaps.Developed interactive Power BI dashboards to visualize workforce metrics, performance indicators, and high-attrition areas.Created fraud detection models using Python and Scikit-learn; performed preprocessing, feature scaling, and evaluation (precision, recall, F1-score)., Strengthened skills in SQL querying, data preprocessing, visualization, and model evaluation through hands-on project work.
Gained practical exposure to Generative AI, neural networks, and LLM concepts applied to business workflows.Built and extended SAP applications using SAP CAPM, SAP Build Process Automation, and BAS.Implemented AI Agents, RAG, and prompt engineering to support SAP S/4HANA workflow optimization.Collaborated on integrating analytics and automation features into SAP-based applications.
Built end-to-end analytics and ML projects including Credit Card Fraud Detection and HR Analytics Dashboard.
Cleaned, processed, and analyzed 1K+ HR records using Excel and SQL Server to identify attrition trends and salary gaps.
Developed interactive Power BI dashboards to visualize workforce metrics, performance indicators, and high-attrition areas.
Created fraud detection models using Python and Scikit-learn; performed preprocessing, feature scaling, and evaluation (precision, recall, F1-score).
Strengthened skills in SQL querying, data preprocessing, visualization, and model evaluation through hands-on project work.
Tools: Python, Pandas, NumPy, Scikit-learn, Matplotlib Developed predictive models using Logistic Regression and Random Forest to classify fraudulent and legitimate transactions. Conducted exploratory data analysis, feature engineering, and model evaluation using precision, recall, F1-score, and accuracy metrics.Implemented automated prediction logic to simulate real-time fraud detection scenarios. •Improved fraud identification reliability through model tuning and performance comparison.
Analyzed 1,000+ employee records to identify trends in attrition, performance, and compensation across departments.Designed KPI-driven Power BI dashboards to monitor workforce distribution, attrition rate, and salary gaps, enabling management to take data-informed decisions. Performed data cleaning, transformation, and validation using Excel and SQL to ensure reporting accuracy and consistency.Delivered actionable insights highlighting high-attrition roles and underpaid job bands, supporting HR planning and retention strategies.
Built an end-to-end complaint analytics solution to automatically categorize customer issues and route them to relevant departments.Processed unstructured complaint text data using Python and NLP techniques to extract meaningful insights.Designed operational Power BI dashboards to track complaint volume, resolution status, and department-wise trends in real time.Reduced manual complaint routing time from hours to seconds through automated classification, improving response efficiency and visibility.Collaborated on frontend (SAP UI5) and backend (SAP CAPM) integration to deliver a production-style analytics workflow.
The AI-first Recruitment Operating System that unifies and automates the entire hiring lifecycle for modern enterprises worldwide.
Dr Job FZ LLC. 2026 © All Rights Reserved
