Data Analytics

• Conducted data analysis and generated actionable insights to support business decision-making processes. • Developed and maintained data pipelines, automated data collection, and data cleansing processes. • Utilized SQL to query databases and extract relevant data for analysis. • Performed exploratory data analysis (EDA) to identify trends, patterns, and outliers in datasets. • Created interactive data visualizations using tools such as Tableau to present findings to managers and head officer. • Collaborated with cross-functional teams to define analytical requirements and deliver data-driven solutions. • Assisted in implementation of machine learning models for predictive analytics and data forecasting. • Conducted data mining and statistical analysis to uncover actionable insights. • Prepared regular reports and dashboards to communicate analysis results to management. • Contributed to the development and maintenance of data analytics tools and dashboards. • Assisted in data-driven decision-making through data interpretation and recommendations. • Identified and addressed data quality issues to ensure data accuracy and reliability. • Supported ad-hoc data analysis requests from various departments within the organization. • Stayed updated with the latest data analytics tools and techniques to improve analytical capabilities. • Performed Descriptive Statistics. • Performed Inferential Statistics. • Performed forecasting activities. • Assisted in risk model development activities. • Monitor Expected Credit Loss (ECL) against the bank's actual credit losses. • Regularly track the performance of key credit risk models, including Probability of Default (PD), Exposure at Default (EAD), and Loss Given Default (LGD), comparing them to actual outcomes. • Performed monitoring of Anti-Money Laundering (AML) alerts and updated thresholds as necessary to maintain compliance and improve detection accuracy.

• Conducted data analysis and generated actionable insights to support business decision-making processes. • Developed and maintained data pipelines, automated data collection, and data cleansing processes. • Utilized SQL to query databases and extract relevant data for analysis. • Performed exploratory data analysis (EDA) to identify trends, patterns, and outliers in datasets. • Created interactive data visualizations using tools such as Tableau to present findings to managers and head officer. • Collaborated with cross-functional teams to define analytical requirements and deliver data-driven solutions. • Assisted in implementation of machine learning models for predictive analytics and data forecasting. • Conducted data mining and statistical analysis to uncover actionable insights. • Prepared regular reports and dashboards to communicate analysis results to management. • Contributed to the development and maintenance of data analytics tools and dashboards. • Assisted in data-driven decision-making through data interpretation and recommendations. • Identified and addressed data quality issues to ensure data accuracy and reliability. • Supported ad-hoc data analysis requests from various departments within the organization. • Stayed updated with the latest data analytics tools and techniques to improve analytical capabilities. • Performed Descriptive Statistics. • Performed Inferential Statistics. • Performed forecasting activities. • Assisted in risk model development activities. • Monitor Expected Credit Loss (ECL) against the bank's actual credit losses. • Regularly track the performance of key credit risk models, including Probability of Default (PD), Exposure at Default (EAD), and Loss Given Default (LGD), comparing them to actual outcomes. • Performed monitoring of Anti-Money Laundering (AML) alerts and updated thresholds as necessary to maintain compliance and improve detection accuracy.