I help software and data systems work reliably at scale.
QA analyst, data researcher, and IT consultant focused on finding defects early, validating data integrity, and verifying systems before they reach users.
Bridging hands-on quality engineering with doctoral research in predictive machine learning for software reliability.
Years of Professional Experience
Test Cases Executed
Records Analyzed
Website Visits
LiveFrom organizational operations to doctoral computer science.
Each step deepened the ability to spot system risk early - from people and process, through IT support and data quality, into software QA and predictive research.
- Step 1
Human Factors & Organizational Operations
British IELTS Mock Test Center · HR Manager
I managed operations, recruitment, and employee support for 25+ team members. My first foundational skill was understanding how people interact with systems, clear communication, and process accountability.
- Step 2
Frontline IT Systems & User Environments
Washington University of Science & Technology · IT Assistant
At the university, I stepped deep into hands-on technology: supporting 100+ students and faculty, resolving 250+ technical requests, and configuring 75+ workstations, security access, and campus network nodes.
- Step 3
Enterprise Data Quality & Analytics
TaskInspota Inc. · Data Analyst
I validated, cleansed, and analyzed 30,000+ records across 20+ datasets. Using SQL, Python, and Excel, I learned how messy raw data creates silent system failures, and how rigorous validation protects critical business decisions.
- Step 4
Software Quality Assurance & Test Engineering
UpSkill Consultancy · IT Consultant & QA Analyst
I took charge of software reliability: designing and executing 150+ manual and automated test cases, tracking 60+ bugs to resolution in Jira, and ensuring smooth delivery across 15+ release sprint cycles.
- Step 5
Doctoral Research & Intelligent Software Reliability
Doctor of Computer Science (DCS) · WUST
Today, I conduct doctoral research combining machine learning with agile CI/CD pipelines to forecast regression defects before deployment, publishing peer-reviewed research in software engineering.
Software I work with every day
From designing test matrices and executing regression suites to writing SQL queries and training defect forecasting models.
Software Quality & Testing
- Manual Testing
- Automated Testing
- Regression Testing
- Jira
- Selenium
- Playwright
- Test Case Design
- Defect Tracking
- User Acceptance Testing (UAT)
Data Analytics & Validation
- SQL
- Python (Pandas)
- Microsoft Excel
- Tableau
- Data Cleansing
- Anomaly Detection
- Schema Validation
- Power BI
IT Systems & Architecture
- Linux Environments
- Windows Server
- Git & GitHub
- System Configuration
- User Access Controls
- Technical Documentation
Research & Intelligent Systems
- Doctoral Research
- Predictive Defect Models
- CI/CD Pipelines
- Technical Writing
- Peer-Reviewed Publishing
- Agile / Scrum
Proven outcomes, described in plain language
A few examples of high-impact work across software testing, data analysis, and technical environments.
AI Capital Readiness Score Validation
Validated assessment flows, scoring logic, and founder-facing recommendations for NSCR - an AI-powered platform that evaluates startup funding readiness across investor criteria.
150+ Test Cases & Agile Release Validation
Designed and executed comprehensive manual and automated test suites covering functional, regression, and user acceptance criteria across 15+ release sprint cycles, catching 60+ critical defects before deployment.
30,000+ Record Cleansing & SQL Anomaly Validation
Built automated SQL checks and Python cleaning pipelines across 20+ heterogeneous datasets, assessing missing values, referential integrity, and delivering 25+ business intelligence reports.
Machine Learning Defect Prediction in Agile QA
Peer-reviewed research investigating predictive commit classification and code complexity metrics inside CI/CD pipelines to forecast regression defects with an 18% improvement in early defect discovery.
QA & analytics templates you can use today
Structured worksheets for test matrices, defect tracking, and data audits. Preview the layout or download directly.
Software QA Test Case Template
Plan, document, execute, and monitor software test cases using a structured quality assurance worksheet.
Software Defect & Bug Tracking Template
A structured tracker for documenting, prioritizing, assigning, and monitoring software defects.
Data Quality & Validation Checklist
A reusable framework for assessing data completeness, accuracy, consistency, duplicates, missing values, and analytical readiness.
Data Analysis Project Tracker
Manage an analytics project from data collection and cleaning through exploration, visualization, findings, and reporting.
0+ professional templates downloaded by QA testers & data analysts so far
Let's start a conversation
Open to QA consulting, analytics reviews, or doctoral research collaboration.
I am actively engaged in consulting, contract QA execution, enterprise data audits, and scientific academic collaborations.
- Software Quality Assurance & UAT
- Automated Regression Test Suites
- Enterprise SQL Data Cleansing
- Defect Prediction Machine Learning
- Doctoral Research & Publications
- Agile Sprint Release Validation
- Technical Problem Solving & Support
Reliable technology isn't an accident. It is verified.
Quality software and trustworthy data come from structured testing, early risk detection, and rigorous validation.
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Portfolio visits
Seeded baseline · keeps counting