Quality, automation, and data services built around practical delivery.

Manual and structured QA support focused on functional quality, release confidence, and clearer defect visibility.

• Test planning and test case design
• Functional and regression testing
• Smoke and sanity validation
• Exploratory testing for risky workflows
• Bug reporting, defect tracking, and retesting
• Release readiness and pre-deployment checks
• Requirement review from a QA perspective

Automation support for teams that want more reliable coverage, less repetitive manual effort, and better confidence around critical journeys.

• Web test automation with Selenium
• Mobile automation support with Appium
• API testing and workflow validation
• Automation framework setup and cleanup
• Reusable test script design
• Critical user journey automation
• QA process improvement and mentorship support

Applied data science work for teams that need cleaner datasets, stronger features, and practical modeling support instead of overcomplicated theory.

• Data cleaning and preprocessing
• Feature engineering for predictive work
• Exploratory data analysis for pattern discovery
• NLP preparation and text data structuring
• Model comparison and baseline evaluation
• Research support with structured datasets
• Problem framing for practical ML projects

Analysis and reporting support for teams that need clearer numbers, sharper insights, and more dependable business visibility.

• SQL-based analysis and reporting
• Python analysis with Pandas and NumPy
• Dashboard and reporting support
• Sales, inventory, and operational analysis
• Data quality checks and transformation
• Web scraping for structured research datasets
• Documentation and insight summaries for stakeholders