PROFESSIONAL SUMMARY
Investment Automation Engineer with expertise in data engineering, financial analysis, and process
optimization. Passed CFA Level III with a background in statistics and investments. Skilled in developing
data pipelines, automating reporting systems, and implementing machine learning models that drive business
efficiency and accuracy. Demonstrates strong technical proficiency in C#, PostgreSQL, Python, and Power BI,
combined with a proven track record of reducing operational costs and enhancing client deliverables.
EXPERIENCE
Analytics Consulting
May 2024 - Present
Investment Automation Engineer
-
Built and maintained various data pipelines using C# and PostgreSQL. This included making
improvements to existing pipelines, fixing bugs, and building a new data pipeline that fetched
data from an API and stored it into a data warehouse.
-
Designed and implemented a report distribution system, used to efficiently and accurately send
different file types to clients after certain checks have been performed. This project reduced
the chance of human error when sending client-facing reports.
-
Streamlined a monthly client report that took hours to create and reduced that time to minutes.
This enabled the team to run the report weekly which was not plausible before. This provided
greater benefits to our clients and created a cost saving in time spent internally.
TecEx
Jan 2023 - Apr 2024
-
Designed an efficient workload allocation system for optimizing team
productivity and
balancing
tasks across a large team.
-
Contributed to developing a dynamic Excel model for analyzing key product
price changes,
improving decision-making and pricing strategy insights.
-
Guided junior analysts in data analysis and modeling techniques, nurturing
their
professional
skills while enhancing the precision and quality of their output.
TecEx
Aug 2021 - Dec 2022
-
Nominated for the 'Rising Star' award, which recognizes exceptional
performance within the
first
18 months of employment.
-
Developed and implemented a data mining and machine learning model in
Python to improve
quoting
accuracy for the freight division, reducing the overall quoting error to
within 10%
-
Streamlined strategic decision-making in various business units using
Power BI, enhancing
metric
definition and reducing monthly reporting time.
EDUCATION
Stellenbosch University, South Africa
2020
Bachelor of Commerce Honours in Statistics
-
Completed modules in data mining, time-series, stochastic
simulation, and programming in R.
-
Exploring the Effect of Prescription Medication on Adverse Events
with Statistical Learning,
using Gradient Boosted decision trees (XGBoost)
- Weighted Average Mark: 72% (Three Distinctions)
Stellenbosch University, South Africa
2016 - 2019
Bachelor of Commerce in Investments and Statistics
- Completed modules in mathematics, statistics, economics, finance, and
programming in SAS and
R.
- Earned Dean’s Merit List for five modules in Investment Management and
Financial Management,
ranking in the top 10% of the class.
- Weighted Average Mark for Undergraduate: 65%
Kearsney College, South Africa
2011 - 2015
- Weighted Average of 79% for matric.
- Engaged in 126 hours of community service.
AWARDS
Member of Golden Key International Honour Society - 2021
Employee of the Month - TecEx - 2021
PROFESSIONAL DEVELOPMENT
Quantitative Analyst with R Track - 2021
Bloomberg Market Concepts Course - 2019
Factset Core Certification Program - 2019
Dale Carnegie - Generation.Next Course - 2019
TECHNICAL STRENGTHS
Software & Tools: Python, C#, Power BI, SQL, HTML, CSS, MS Offce, Bloomberg,
FactSet, LaTeX
PERSONAL TRAITS
- Quick and eager learner with a talent for adapting to new software and
platforms, demonstrating a
rapid
learning ability.
- Collaborative team player, actively contributing to idea generation and
fostering a positive and
collaborative
work environment.
- Passionate about capital markets and leveraging quantitative methods to
enhance decision-making.