ALM Mathematical Statistics and Market Research.
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Lesedi Kopeledi Matshehla is a resident of Thatch Hill Estate at Centurion in the Gauteng province city of Pretoria. She has been working in the Banking-finance occupational sector for more than 8 years. Currently she is employed at FirstRand group.
Highest qualification passed is BSC Honours in Mathematical Statistics. This supports an enthusiasm to grow her career and work experience through job opportunity offer in the industry of quantitative and qualitative market production to manufacture goods and services for a balanced and efficient economic growth. Analysis of clients' credit affordability is an important matter that can increase development of property, employment, production, infrastructure, and other basic needs such as school education, hospital health, supermarket food, water supply, dealership vehicles and retail clothes.
Corporate work at FirstRand developed my growth of being a competent and experienced individual to interpret and allocate distribution of goods and services to achieve a stable market industry. I am ready to apply SQL, SAS enterprise, Microsoft Office, computing programming languages and team-work skills while developing additional skills and knowledge with the opportunity to find a job position at ABSA. Being a worker means a lot of responsibility to take care of a medium source of exchange required by technical businesses and people who need to utilize production.
The research report topic of BSC Honours in Mathematical Statistics at University of Pretoria has motivated me to advance my career in quantitative and qualitative data analysis. I have greatly enjoyed the challenges that came with writing the research report and realized that pursuing a career in data science will really define the type of a person I am as well as my career path.
The topic of my research was: the optimal scaling technique for the analysis of multivariate categorical data. In summary, the purpose of the report was to convert a categorical data set collected by a questionnaire into quantitative data set so that I can perform a correspondence analysis on a contingency table.
