
M. Ejaz
Financial and Operational Data Analyst
Habilidades

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Portfólio
Experiência profissional
Data Analyst
Gravo • Período integral
May 2025 - Present • 1 yr 2 mos
• Monitored and analyzed ATM/MCDM performance data, applying trend analysis to help maintain 99% network uptime. • Investigated transaction failures and connectivity issues by mining system logs and operational datasets to identify root patterns. • Built daily performance dashboards tracking machine health, fault frequency, and resolution time, turning raw log data into clear operational insights. • Conducted root cause analysis using data-driven methods, reducing recurring hardware/software issues by 15%. • Partnered with operations and engineering teams, delivering data insights that improved incident response speed and accuracy.
Data Analyst
DecoHindi • Meio período
May 2026 - Jun 2026 • 1 mo
• Completed a hands-on Data Analytics internship at DecodeLabs, delivering 5 real-world projects spanning data cleaning, EDA, SQL analytics, and Power BI reporting. • Built interactive Power BI dashboards to analyze sales and order data, surfacing trends to support business decisions. • Developed KPI reports, transforming raw datasets into clear, actionable insights using SQL, Excel, and Power BI.
Data Analyst
Nexus • Freelance
Oct 2025 - Dec 2025 • 2 mos
• Data Preparation & Quality: Collected, cleaned, and standardized structured and semi-structured datasets using Python (Pandas, NumPy) and SQL, ensuring accuracy and consistency for downstream analysis. • Exploratory Analysis: Conducted EDA to uncover trends, anomalies, and key business drivers, directly informing data-driven decisions. • Predictive Modeling: Built and evaluated regression and classification models in Scikit-learn to solve real-world business problems. • Feature Engineering: Engineered and transformed features to improve model performance and analytical reliability. • Visualization & Reporting: Designed dashboards and reports in Python, Tableau, and Power BI to translate complex findings into clear, actionable stakeholder insights. • Cross-Functional Collaboration: Partnered with senior analysts to align analytical outputs with business objectives and real-world use cases. • End-to-End Ownership: Managed full analytics workflows, from data acquisition and cleaning through modeling, validation, and insight delivery.