Wasay Mohammed

• Automated ingestion of multi-source data by designing 15 modular ETL pipelines in Python & Airflow, implemented retry logic, dynamic scheduling, and data validation boosting data accuracy by 40% and shortened reconciliation time by 25%
• Reviewed and verified financial and operational datasets to ensure compliance with client standards and regulatory requirements.
• Optimized Snowflake pipelines using clustering & partitioning, supporting real-time dashboards and reduced average query latency by 30%, improving executive reporting speed.
• Deployed CI/CD workflows with GitHub Actions and automated testing & deployment, shortening release cycles by 20% and enhancing deployment consistency.
• Developed Python-based data monitoring scripts to detect anomalies and schema drift, proactively addressed data quality issues and minimized downtime incidents.
• Led Agile sprint ceremonies (planning & retrospectives) using Jira, coordinated with engineers, analysts, and PMs to improve cross-team alignment and reduced bug resolution time by 18%.

• Analyzed 80K+ loan applications using Python & SQL, performed scenario & stress testing for risk evaluation.
• Executed A/B tests on credit scoring models to refine predictive accuracy and supported data-driven lending strategies.
• Presented dashboards & insights to non-technical stakeholders for data-based decision making.
• Automated credit risk reporting with Power BI dashboards backed by AWS Redshift to removed manual updates and saved 30% of reporting effort and improved data freshness.
• Built and optimized ETL pipelines for extracting, transforming, and loading customer risk data into AWS Redshift, improving data processing speed by 30%.

HR Database Management System | Bachelor's Project

• Developed a centralized HR database system for a university, improving data accessibility and accuracy utilizing Java
• Implemented structured data storage and validation, reducing HR data entry errors by 30%.
• Integrated SQL databases for efficient record management and reporting.
• Built Power BI dashboards, reducing HR report generation time by 40%.

Predictive Analytics for Optimizing Inventory Management | Master's Project

• Developed a predictive model that reduced stockouts by 25% and improved inventory turnover by 18%, boosting revenue.
• Analyzed five years of sales data (500K+ transactions) to identify demand trends.
• Integrated the model into a SQL-based inventory system for automated demand forecasting.
• Created an interactive Power BI dashboard to visualize real-time inventory trends.

Synthetic Data Generator for Privacy | Personal Project

• Created a synthetic data tool that mimicked real datasets with 95%+ fidelity, enabling safe use of sensitive data.
• Built the solution using Python, CTGAN, and AWS (S3 + Lambda), applying privacy filters that reduced identifiable attributes.