About
B.Tech graduate in Artificial Intelligence & Machine Learning with hands-on experience in data analysis, business intelligence, dashboard development, and reporting. Skilled in Microsoft Excel, SQL, Power BI, Tableau, and Python for data cleaning, validation, visualization, and business analytics. Experienced in building interactive dashboards, analyzing datasets, and generating actionable insights through academic and personal projects. Strong analytical mindset, problem-solving abilities, and attention to detail with a passion for supporting data-driven business decisions.
Skills & Expertise (41)
Work Experience
HR Attrition Dashboard Developer
GitHub
Present - Present
Developed an interactive Power BI dashboard to analyze employee attrition, workforce demographics, and departmental performance metrics. Performed data cleaning, validation, and transformation to ensure accurate and consistent reporting. Designed KPI scorecards, trend analysis reports, and interactive dashboards for management review. Generated actionable business insights through workforce analytics and performance monitoring. Created automated reporting views that improved accessibility and efficiency of HR reporting processes.
Fraud Detection Dashboard Developer
GitHub
Present - Present
Built an end-to-end fraud analytics and prediction platform using Python, SQLite, XGBoost, and Streamlit to analyze large-scale financial transaction data. Developed SQL-based data extraction, cleaning, validation, transformation, and aggregation workflows to support fraud monitoring, trend analysis, and business reporting. Trained and evaluated an XGBoost classification model using ROC-AUC, confusion matrix, and feature importance analysis to improve fraud detection accuracy. Designed an interactive dashboard featuring KPI tracking, fraud trends, loss analysis, sender risk profiling, and real-time fraud prediction capabilities.
Customer Segmentation Analysis Developer
GitHub
Present - Present
Developed a customer segmentation application using Python, Streamlit, Pandas, and Scikit-learn to analyze customer behavior and support data-driven marketing strategies. Implemented K-Means clustering on customer demographic and spending data to identify distinct customer groups based on age, annual income, and spending patterns. Performed data preprocessing, feature selection, and exploratory data analysis to improve clustering effectiveness and business interpretability. Built interactive visualizations and cluster analysis dashboards using Matplotlib and Seaborn to communicate customer insights effectively. Enabled automated customer segmentation through a web-based interface with dataset upload, cluster configuration, and downloadable analytical outputs.
Education
B.Tech in Artificial Intelligence & Machine Learning - Sagar Institute of Research and Technology
2022 - 2026 · Afghanistan
Class XII — PCM - D. M. P. G. I. College
- 2022 · Afghanistan
Certifications
Azure Machine Learning Studio
SAGE Summer School (The SAGE Group) · 2025
Deloitte Data Analytics Job Simulation
Deloitte (Forage) · 2025
Python and SQL for Data Science
Scaler Topics · 2025
Python Course for Beginners with Certification: Mastering the Essentials
Scaler Topics · 2024
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Open to Relocation
Skills (41)
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