Econometrics | Data Science | Financial Engineering Candidate
Based in Johannesburg, South Africa
I’m a driven, inquisitive, and creative thinking professional seeking to leverage skills attained from my studies and part-time work experience. I have prepared well for a career in Investments and Securities, Econometrics and Data Science disciplines as well as general manufacturing and service firms that seek and rely on the expertise of a role with a quantitative background. These skills also include strong interpersonal and task prioritization skills. In addition, working under pressure, flexibility and in teams were critical in succeeding in both my academics and roles in part-time work. My philosophy in work is to be an asset to add value that best enhances the organizational brand and value proposition in what I do and wherever I am.
HOUSING IN MEXICO
For each assessment, students must score 90% Learners use a dataset of 21,000 properties to determine if real estate prices are influenced more by property size or location. They import and clean data from a CSV file, build data visualizations, and examine the relationship between two...
APARTMENT SALES IN BUENOS AIRES
For each assessment, students must score 90%. Learners build a linear regression model to predict apartment prices in Argentina. They create a data pipeline to impute missing values and encode categorical features, and they improve model performance by reducing overfitting. -Loaded multiple...
AIR QUALITY IN NAIROBI
For each assessment, students must score 90%. Used a dataset from one of Africa's largest open data platforms, openAfrica. Learners build an ARMA time-series model to predict particulate matter levels in Kenya. They extract data from a MongoDB database using pymongo, and improve model...
EARTHQUAKE DAMAGE IN NEPAL
For each assessment, students must score 90%. Learners build logistic regression and decision tree models to predict earthquake damage to buildings. They extract data from a SQLite database, and reveal the biases in data that can lead to discrimination. -Queried an SQL database. -Performed a...
BANKRUPTCY IN POLAND
For each assessment, students must score 90%. Learners work with financial data from the Emerging Markets Information Service to look at financial indicators from Poland and Taiwan and build models to predict whether a corporation will go bankrupt.
CUSTOMER SEGMENTATION IN THE US
For each assessment, students must score 90%. Learners work with consumer finance data from the US Federal Reserve to identify households that have a hard time getting credit. There after, they build an unsupervised model to segment households and finally create an interactive dashboard.
A/B TESTING AT WORLDQUANT UNIVERSITY
For each assessment, students must score 90%. Learners design and conduct an A/B test to improve quiz completion for enrollment at WQU. They build custom Python classes to implement an ETL process, and they create an interactive data application following a three-tiered design pattern.
2016 - 2021