M A RAHMAN

DATA & BUSINESS ANALYST

Predictive Modeling | Workflow Automation | Strategic Intelligence

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FEATURED IMPACT METRICS

Key Performance Indicator	Achievement	Business Unit
Conversion Optimization	25% Increase in Trial-to-Paid Conversion	PDA Infotech
Operational Efficiency	60% Reduction in Manual Reporting Effort	PDA Infotech
Forecasting Precision	85% Accuracy in Stock Trend Predictions	AI Variant
Resource Optimization	12% Reduction in Grid Management Costs	AI Variant
Risk Reduction	18% Decrease in Financial False Positives	AI Variant

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PROFESSIONAL EXPERIENCE

DATA ANALYST | PDA INFOTECH

Dubai, UAE | Nov 2024 – Present

• Predictive Analytics Deployment: Engineered and deployed machine learning frameworks for Churn, CLV, and Segmentation, directly generating AED 150K in quarterly revenue and improving retention by 18%.
• BI Infrastructure: Architected high-performance Power BI data models using DAX and Power Query to deliver KPI-driven insights for C-suite and board-level reporting.
• ETL Engineering: Automated complex data workflows via Google BigQuery and Python, enhancing data governance while slashing manual labor by 60%.
• Strategic Advisory: Partnered with Finance and Product teams to translate complex analytics into actionable ROI-improving strategies and long-term budgeting.

DATA SCIENCE INTERN | AI VARIANT

Hyderabad, India | Jun 2023 – Aug 2024

• Market Intelligence: Collaborated with BlackRock to build LSTM, ARIMA, and Prophet forecasting models for international markets, achieving a 15% reduction in RMSE.
• Energy Analytics: Developed an 88% accurate solar power prediction model for Cygni Energy, optimizing resource allocation and reducing operational costs by 6%.
• Automated Intelligence: Designed Selenium-based web scraping tools for real-time sentiment analysis, improving classification accuracy by 10% through advanced feature engineering.

BUSINESS ANALYST | AMAZON

Hyderabad, India | May 2022 – May 2023

• Process Automation: Spearheaded Excel macro implementation for Seller Flex and daily operations, increasing process efficiency by 10–15%.
• Data Integrity: Leveraged Hubble Query Language and ETL processes to enhance catalog management precision, data flow, and reporting reliability.

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TECHNICAL PROJECT PORTFOLIO

1. BANKRUPTCY PREVENTION & RISK ASSESSMENT

• Overview: Engineered an ensemble system (Logistic Regression, Random Forest, Gradient Boosting) to identify financial distress in firms.
• Impact: Reduced false positives by 18% and improved overall prediction accuracy by 22%.
• Links: GitHub Repository | ▶️ Watch Project Demo

2. APPLE STOCK FORECASTING (TIME SERIES)

• Overview: Developed a high-precision framework using LSTM and Prophet to predict market trends and equity volatility.
• Impact: Achieved a 15% RMSE reduction compared to baseline models with 85% prediction accuracy.
• Links: GitHub Repository | ▶️ Watch Project Demo

3. NLP SENTIMENT & CUSTOMER INTELLIGENCE

• Overview: Built end-to-end NLP pipelines using NLTK and Selenium to analyze and classify Amazon customer reviews.
• Impact: Realized a 20% increase in sentiment classification accuracy for targeted marketing insights.
• Links: GitHub Repository | ▶️ Watch Project Demo

4. SOLAR POWER PREDICTION & DEPLOYMENT

• Overview: Created an ML solution using XGBoost to estimate solar energy output, deployed via a Streamlit dashboard.
• Impact: Achieved 88% accuracy, contributing to a 12% reduction in operational grid management costs.
• Links: GitHub Repository | ▶️ Watch Project Demo

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ACADEMIC BACKGROUND

• B. Tech in Mechanical Engineering
• Jawaharlal Nehru Technological University (JNTU) Hyderabad
• Classification: First Class | 2015 – 2019

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PROFESSIONAL CERTIFICATIONS

• Master’s Program in Data Science | NASSCOM, Government of India
• Data Science Certification | ExcleR Solutions
• Machine Learning with Python | IBM Developer Skills Network
• Python 101 for Data Science | IBM Developer Skills Network