Sandisiwe Mtsha Email & Phone Number

Johannesburg, Gp, Za

Pretoria, Gauteng, South Africa

- Utilized Power BI to analyze book and consultant performance data, providing valuable insights for informed decision-making.- Worked collaboratively with teams to identify areas for improvement based on consultant performance metrics.- Conducted data cleansing and modeling to ensure accuracy and meaningful analysis.- Assisted in developing and implementing data-driven solutions for client projects.- Created dashboards and reports for stakeholders, enhancing data-driven decision-making.- Engaged in training to continuously improve proficiency in data analysis tools and techniques.- Collaborated with the team on testing and modifying the environment for optimal performance.- Contributed to building a dashboard for daily reports with automated hourly updates, streamlining data presentation and accessibility.

Pretoria, Gauteng, South Africa

- Performance Reporting: Help generate regular performance reports by analyzing key metrics like call volumes, average handling times, and customer satisfaction scores, providing insights for optimizing call center operations.- Data Visualization: Assist in creating dashboards and visualizations using tools like Power BI and Excel to present complex data in a clear and accessible manner for decision-making.- Trend Analysis: Work with senior analysts to identify trends and patterns in call center data, such as call centre agents perfomance, to recommend improvements in resource allocation and service delivery.

Remote

- Preprocessed structured and unstructured data using Python, R, and SQL.- Developed predictive models and machine learning algorithms to tackle business challenges.- Presented insights via Tableau and Power BI.- Collaborated with cross-functional teams on data-driven solutions.- Conducted credit risk analysis.- Predicted insurance claims using Logistic Regression, XGBoost, and Random Forest, with XGBoost improving accuracy.Worked on a project for an insurance company, predicting client claims, which resulted in a 15.6% reduction in monthly claims by optimizing installment allocation.I worked on a project for an insurance company aimed at predicting whether clients would file a claim. My role involved preprocessing data to ensure accuracy, performing exploratory data analysis to identify key patterns, and engineering features to enhance model performance. Collaborated and built and evaluated several predictive models, including Logistic Regression, Random Forest, and XGBoost, with XGBoost proving to be the most accurate. This project led to a 15.6% reduction in the number of clients filing claims per month by optimizing installment allocation based on predictive insights, thereby significantly improving the company’s risk management strategy.

•Managed branch operations, including reviewing and disbursing loan applications with sales and collection targets.• Developed and implemented sales strategies like social media, government departments presentations to achieve sales targets.• Achieved the 2nd highest collection percentage provincially, properly scrutinising bank statements of clients before disbursement.• Utilized problem-solving skills to resolve customer complaints and staff issues amongst themselves and when issue is with the staff and client

• Processed loans and provided financial education to clients• Achieved high collection percentage through effective communication, negotiation skills, and credit risk analysis

Master'S Degree, Masters Of Science In Applied Statistics

# Advanced Multivariate Statistical Analysis # Advanced Experimental Design #Applied Non- Parametric Statistics # Dissertation: Comparison.

Certificate, Data Science

* Gathering and Managing Data * Analytical Programming * Data Visualisation * Machine Learning * Model Deployment * THRIVE (Soft Skills)

Honours, Applied Statistics

* Multivariate Statistics Analysis and Applied Multivariate Statistics * Fixed and Random Effect Modelling * Applied Time Series *.

Bsc, Mathematics And Statistics