Farisani Mulaudzi

Extracted and aggregated data from large-scale relational databases for advanced data analysis.
Demonstrated expertise in coding yield optimization models using different statistical techniques.
Leveraged statistical analysis and forecasting techniques to support trading desk and Portfolio Managers.
Utilized statistical analysis and machine learning techniques to forecast and interpolate Credit Default Swap prices.
Ensured accuracy and integrity of data through SQL queries and database management.
Created web-based investment dashboards and pages using Flask, FastAPI, HTML, CSS, and JavaScript for real-time performance, positioning, and risk monitoring.
Managed and collaborated on version-controlled repositories using Git for seamless team collaboration and efficient code management.
Performed quantitative research and implemented the research.
Conducted regular code reviews and implemented code enhancements to ensure optimal performance and maintainability.
Conducted regular data analysis and performance evaluation to optimize trading strategies.

Data Analysis: I analyze data to extract meaningful insights and patterns, often using Python for data manipulation and statistical analysis.

Model Development: I build and fine-tune quantitative models to forecast market behavior, optimize strategies, and achieve better outcomes.

Software Development: I engage in software development, including web applications, using technologies like HTML, CSS, and JavaScript, to create tools that enhance optimization.

Optimization: I actively seek opportunities to optimize strategies, portfolios, and data-driven models to improve overall performance.

Performance Monitoring: I continuously monitor and evaluate the performance of financial and statistical models, making adjustments for optimization.

Collaboration: I work in teams to ensure data quality, optimize data-driven models, and conduct regular data analysis, seeking ways to improve processes and results.

Problem Solving: I address complex problems by applying quantitative and programming skills, focusing on optimization as a key objective.

These tasks collectively represent my role as a quantitative analyst, with a strong emphasis on data analysis, model development, software development, and optimization to drive better outcomes.

Imported and maintained performance databases.
Maintained data for Global Investment Performance Standards (GIPS) audits.
Created risk, attribution, time series, and periodic reports.
Calculated and verified performance returns and risk of portfolios using different valuation methodologies.
Conducted daily, weekly, monthly, quarterly, and yearly performance and risk analysis on portfolios and securities to assist the investment team as well as the dealer's desk.
Calculated and verified performance returns and risk of portfolios based on different valuation methodologies.

Cleaned and performed quality checks on a dataset with over 3,000,000 data points.
Conducted data analysis to detect fraud among 15,000 employees.
Identified anomalies based on participating data, including geographical and individual anomalies.
Created models to predict future occurrences.
Presented findings to the CSIR and data custodians.
Identified 100% of employees defrauding the data custodians.