أنجالي Jayan

• Analyzed data using SQL, Excel, and Power BI to identify business trends and
support decision-making.
• Managed ETL processes and integrated data from multiple sources to ensure data

• Work with project managers and department heads to understand analytics needs
and deliver timely insights. Collect, organize, and maintain data from primary and
secondary sources while ensuring quality and accuracy.
• Clean, prepare, and validate data sets for reliable analysis and reporting. Leverage
Excel for data wrangling, reporting, and dashboard creation, and Use python for
deeper statistical analysis and predictive modelling.
• Build dashboards, charts, and reports that simplify data findings for both technical
and non-technical audiences. Develop and automate processes for data collection,
integration, and reporting to improve efficiency.
• Collaborate with cross-functional teams to align data-driven insights with
organizational goals.

• Provide comprehensive administrative support, including managing calendars,
scheduling meetings, and handling correspondence.
• Prepare reports, presentations, and other documents as required.
• Perform data analysis using tools such as Excel and Power BI to identify trends and
insights.
• Coordinate effectively with various teams to ensure smooth operational flow and

• structured and unstructured data and statistical
analysis to generate actionable business insights.
• Developed Power BI and Tableau dashboards for KPI reporting, business
intelligence, and performance monitoring.
• Performed ETL processes including data extraction, transformation, validation, and
integration from multiple data sources.

• Performed data cleaning, transformation, validation, and exploratory data analysis
(EDA) using Python and Excel to ensure data accuracy and quality.
• Built predictive machine learning models using Random Forest, Support Vector
Machine (SVM), and Gradient Boosting Machine (GBM) for financial risk analysis.
• Conducted statistical analysis and generated analytical reports with data
visualizations using Python (Pandas, Matplotlib, Seaborn) and Microsoft Excel.
• Analyzed financial datasets to support payment default risk prediction and provide
actionable business insights.

• Delivered mathematics instruction to higher secondary students.
• Maintained academic performance records and reports.
• Strengthened analytical thinking, communication, and problem-solving skills
through teaching and mentoring.