Wasay Mohammed

• Automated routine data processing tasks using SQL and Microsoft Power Automate, reducing manual effort by saving 15+ hours per week.
• Reviewed and verified financial and operational datasets to ensure compliance with client standards and regulatory requirements.
• Developed an automated financial data review and reporting system that enhanced data accuracy by 40% and reduced quarterly reconciliation time by 25%, illustrating strong data modeling and mining capabilities.
• Analyzed over 1 million records to uncover trends and patterns, contributing to a 15% improvement in data-driven decision-making and accelerating project delivery by two weeks.
• Designed and maintained interactive dashboards using Power BI, providing real-time insights and enabling agile responses to business needs.

• Extracted and analyzed data from 500+ credit applications using SQL to assess financial risk metrics and ensure data integrity.
• Led an A/B testing campaign utilizing statistical models to evaluate creditworthiness and support data-driven risk assessment.
• Automated risk reporting processes with Power BI and AWS Redshift, enhancing scalability and efficiency in cloud-based data warehousing.
• Collaborated with cross-functional teams, including finance, analytics, and product management, to drive strategic, data-driven initiatives.
• Conducted stress testing and scenario analysis on 80K+ customer records using Python and SQL queries, ensuring robust risk evaluation.
• Built and optimized ETL pipelines for extracting, transforming, and loading customer risk data into AWS Redshift, improving data processing speed by 30%.

• Executed data extraction and cleaning processes on over 500,000 sales transaction records from SQL databases using Python libraries (Pandas, NumPy), achieving a 99% accuracy rate in data integrity and consistency which facilitated more reliable analytics.
• Conducted comprehensive exploratory data analysis (EDA) involving trend analyses of seasonal sales patterns and correlation studies across 10 key variables, identifying three primary sales drivers that contributed to a forecasted revenue increase of 15% in the next quarter.
• Tracked and analyzed key performance indicators (KPIs) such as customer acquisition cost, average order value, and conversion rates to provide actionable insights.

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.