Work Experience
I am experienced in working with data, be it collecting, cleaning, encoding, storing, wrangling, visualizing, analyzing or imputing data. I can use R, Python, PostgreSQL, Stata, Bash, Markdown, CSS, HTML and LaTeX. From 2019–2023 I worked as an economist in SALDRU—looking at labour and macroeconomic trends in South Africa. I also worked for a behavioural economics consultancy. Through this experience, and my post-graduate Economics courses, I became a proficient statistician, with an understanding of survey design, microeconomics, and time series forecasting. My research simulating earnings cuts during the covid-19 lockdown fed into the national policy debate on the furlough scheme (the Temporary Employer/Employee Relief Scheme (TERS)). I have also researched occupational polarization over time in the South African labour market. A hollowing out of middle-skill occupations has been seen globally, due to automation. My primary supervisor for this paper is Prof Murray Leibbrandt.
Apps that I have experience with include GitHub, VS Code, Google Workspace (including Calendar, Chat, Meet, Sheets and shared drives), Office365, Teams, SharePoint, WordPress, Redmine (project management), Todoist, Notepad++, Typora, and Tableau.
From 2022 I started working in corporate settings, focusing on data skills and programming. From Jan–May 2022, I worked in the FMCG industry as a Junior Data Visualization Developer at DataOrbis (a data analytics company). In that role, I used Tableau to edit and refresh business intelligence (BI) dashboards for retail manufacturers. From May–July 2022, I practiced arbitrage on the cryptocurrency market, using Python.
From August 2022 I started an SA-TIED academic project, which investigates how much South Africans save for retirement, using income tax data at the National Treasury. This is used to comment on the proposed statutory pension scheme, with contributions made through the formal employment system. The Treasury discussion paper is saved at http://www.treasury.gov.za/comm_media/news_archive_2021.aspx (14 Dec 2021). My supervisor for this is Andrew Donaldson.
During a data creation process, I am skilled at documenting metadata, and I have experience with the Statistical Data and Metadata Exchange (SDMX) protocol for storing data.
Since April 2023 I have worked at Codera Analytics, as a software engineer. At Codera, I formulate schema to structure unstructured public-domain economic data. I synthesise and organise messy data, helping to write software that transforms public data (often extracted programmatically). Then I oversee the loading of data into EconData, with help from Byron Botha. Data engineering is very methodical, and requires a high degree of logic. At Codera, I also develop Shiny apps, help with data visualization and blog posts about our data, write documentation (including public docs), train interns, and manage projects.
Education
Courses
I have done introductory courses in Python and SQL (e.g. on DataCamp). The Google Machine Learning documentation ( https://developers.google.com/machine-learning ) is a good place to focus on and learn machine learning—I plan on doing this (my profile).
I aim to work through the Microsoft Azure Data Engineer Associate Certification. My Microsoft Documentation profile is https://docs.microsoft.com/en-za/users/aidanhorn
Data Analysis for Social Scientists
Certificate: https://micromasters.mit.edu/certificate/course/0108499095d2bba92ef743bf1f22d511
University of Cape Town
BSocSci BCom(Hons) MCom Cape Town
Feb 2019 – March 2020: Master of Commerce in Economics
Econometrics, Microeconometrics, Labour Economics, Macroeconomics, Game Theory, Information Economics, Mathematical Economics. Dissertation: Teacher Remuneration in South Africa.
2018: Bachelor of Commerce (Honours) in Economics
Econometrics, Development Economics, Policy Analysis, Labour Economics, International Finance, Behavioural Economics, Macroeconomics, Mathematical Economics. Dissertation: The youth wage subsidy in South Africa.
2014–2017: Bachelor of Social Science (Economics, Mathematics)
3rd year level: Mathematics, Economics (Micro, Macro, Labour, Econometrics), Public Policy.
2nd year level: Mathematics, Economics (Micro, Macro, Development Economics), Public Policy & Administration.
1st year level: Mathematics, Public Administration, Economics, Sociology, Social Development, Statistics, Psychology, Environmental Science, Information Systems.