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amaan qaziAQ
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amaan qazi

@amaanqazi

I validate structured data and build machine learning models for real-world AI impact.

Pakistan
Message

What I'm looking for

I'm looking to contribute to real-world AI and data-focused work where I can apply data validation, analysis, machine learning, and careful guideline-based review to create meaningful impact.

At Simply.TV, I review and validate high volumes of structured content information, ensuring accuracy, completeness, consistency, and correct categorization.

I apply defined guidelines and independent judgment to identify inaccurate, incomplete, and ambiguous records. I flag uncertain cases, collaborate remotely when clarification is needed, and maintain organized digital records across internal systems.

Previously, at Archroma Pakistan Limited, I collected, reviewed, and validated business data for sales and operational reporting. I cleaned and standardized datasets in Excel and Power Query, transforming raw information into consistent formats for recurring reports.

My academic work in AI, big data, data mining, and database systems includes a credit card fraud detection project using Logistic Regression, Random Forest, XGBoost, and SMOTE. I'm interested in contributing to real-world AI that creates an impact.

Experience

Work history, roles, and key accomplishments

AL

Sales Data Analyst Intern

Archroma Pakistan Limited

Jan 2025 - Apr 2025 (3 months)

Collected, reviewed, and validated business data from multiple sources to support accurate sales and operational reporting. Cleaned and standardized datasets using Excel and Power Query, identifying missing, inconsistent, and incorrectly structured information before analysis.

Education

Degrees, certifications, and relevant coursework

Taylor's University logoTU

Taylor's University

Bachelor of Business, Digital Marketing & Analytics

Grade: CGPA: 3.36/4.00

Pursued a Bachelor of Business (Hons) in Digital Marketing & Analytics with a CGPA of 3.36/4.00. Coursework included Principles of Artificial Intelligence, Big Data Management, and Data Visualization.

Tech stack

Software and tools used professionally

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