Sabiha SK

Developed and maintained HR data dashboards and reports to support strategic decision-making using HRIS and Business Intelligence tools. Conducted data cleaning and validation to ensure HR data integrity and accuracy for reporting and compliance purposes. Assisted in the creation of HR metrics and predictive analytics, including turnover analysis and workforce insights. Collaborated with HR Business Partners and leadership to provide ad-hoc analysis on employee engagement, diversity, and compensation trends. Supported quarterly and annual HR data deliverables, including workforce planning, benefits analysis, and HR governance reporting.

• Performed data collection, cleaning, and analysis using SQL, Python, and Excel to ensure data accuracy and reliability. • Created interactive dashboards and reports in Power BI and Tableau to visualize trends and support decision-making. • Applied statistical methods such as regression analysis and hypothesis testing to identify actionable insights from large datasets. • Conducted ETL processes to integrate data from multiple sources into a central repository for analysis. • Automated data workflows using Python scripts, reducing manual reporting time by 30%.

• Collaborated with clients to extract requirements, translating them into actionable logic and visualizations, elevating satisfaction by 20%. • Conducted data analysis using PostgreSQL and Microsoft Excel, executing ETL operations, enhancing data quality through Power BI transformations, driving efficiency. • Engineered intricate visuals and designed Power BI dashboards with D3.js and DAX functions, enriching data presentation, empowering decision-making, and boosting user engagement by 15%. • Managed PostgreSQL databases and APIs, executing 1000+ data queries, optimizing scripts, reducing dataset loading time by 80%. • Streamlined report downloads using Power Automate flows and Power Apps, reducing time by 70%, heightening satisfaction and efficiency. • Leveraged Azure DevOps for issue resolution, task management, bug tracking, and testing, amplifying team productivity by 20%.

• Designed and implemented a custom CRM system, enhancing client engagement by 30% and streamlining data management processes. • Conducted data analysis to identify customer behavior trends, providing insights to improve marketing strategies. • Created dynamic dashboards and reports to track key performance metrics, improving stakeholder visibility into project success. • Collaborated with cross-functional teams to gather and document business requirements, ensuring alignment with user needs. • Applied data modeling techniques to enhance reporting accuracy and optimize decision-making processes.

• Developed an anomaly-based Intrusion Detection System (IDS) to enhance network security and monitor for cyber threats. • Increased threat detection rates by 25% and reduced false alarm rates by 30% through data analysis and pattern recognition. • Implemented machine learning algorithms (Decision Tree, Random Forest, KNN), achieving 98.39% accuracy on the KDD'99 Dataset. • Conducted statistical analysis to identify traffic patterns and anomalies, improving incident response strategies. • Utilized canonical correlation analysis for optimal feature selection, streamlining data processing and enhancing predictive modeling efficiency.