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Data Analyst with less than a year in Python-based analytics & ML model development.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science student with hands-on experience in Python-based analytics, ML model development, and interactive dashboard creation. Proven ability to lead data projects end-to-end from SQL-based cleaning to Streamlit deployment.
Sir Syed University of Engineering & Technology
Bachelor of Science · Data Science
August 1, 2024 – Present
Excelerate
Data Analyst Associate Intern
September 1, 2025 – October 1, 2025
India
EduSense - Classroom Intelligence Platform
January 1, 2026 – Present
Integrated Groq API (LLAMA 3.3 70B + LLAMA 4 Scout Vision) across 6 specialized AI agents including OCR-based assignment grading, bilingual report generation in English and Urdu, and a LangChain-powered natural language chatbot over live student data. Architected a CSV ingestion pipeline with automatic column validation, missing-field inference, and risk score computation making the platform compatible with any teacher's existing gradebook. Built a weighted risk scoring engine (attendance 30%, quiz performance 25%, late submissions 20%, participation 15%) to classify students into High/Medium/Low risk bands with Plotly.
View ProjectProduction Data Platform
January 1, 2026 – Present
Built end-to-end data pipeline using PySpark implementing Medallion Architecture (Bronze/Silver/Gold) to clean and unify 8 messy data sources into a Star Schema. Designed a Gold Star Schema with zero orphan records enforced, computing business KPIs including Return on Ad Spend and Customer Acquisition Cost across 500 transactions and 42 days of data. Built a Lambda Architecture using Python Watchdog for real-time incremental processing - detecting new CSV files, processing only new rows, and upserting into PostgreSQL. Orchestrated the full pipeline using Prefect with enforced dependency ordering.
View ProjectCredit Risk Classification Model
January 1, 2025 – Present
Built and evaluated tree-based models (Decision Tree, Random Forest, Extra Trees) for credit risk classification. Optimized performance using GridSearchCV and selected Random Forest based on validation. Deployed an interactive loan approval prediction app using Streamlit, enabling real-time inference with user-supplied applicant data.
View ProjectData Science
NED University of Engineering & Technology
January 1, 2025 – Present
Data Analysis Using Python
10 Pearls
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's projects show a strong interest in diverse data science applications, from production data platforms to credit risk and educational intelligence. This breadth of interest could indicate adaptability. However, the experience is limited to a single internship and personal projects, which makes it difficult to fully assess cultural fit in a collaborative, professional environment. The psychometric test score being 0 means there is no data to evaluate aspects like team collaboration or work attitude, which are crucial for cultural fit.
Soft Skills & Operational Fit
The candidate demonstrates initiative through leading an intern team and owning end-to-end projects. The project descriptions suggest an ability to work independently and deliver functional solutions. However, the psychometric test score is 0, which indicates insufficient data to assess logical reasoning, work attitude, stress handling, and team collaboration. This is a significant gap in evaluating operational fit.