Richard Ball
Principal Data Scientist
Cape Town, Western Cape, South Africa
Summary
👤
Senior🎓
Top SchoolRichard Ball is a Principal Data Scientist and AI engineer based in Cape Town with a decade of hands-on experience translating research-grade machine learning into production at fintech and data-privacy focused companies. He has led data science teams at Luno and Anonos and now shapes AI strategy and delivery at KINETIC, combining domain expertise in revenue optimisation and financial engineering with a PhD in Computer Science. His background spans industrial engineering through quantitative management and advanced degrees in engineering management, financial engineering and an MBA, which gives him a rare blend of technical depth and product-oriented business judgement. Richard is comfortable moving between research, model deployment and privacy-preserving data solutions, and has repeatedly taken models from prototype to live use in regulated environments. Colleagues would note his pattern of stepping into lead roles at growth-stage teams to institute robust, measurable ML practices while keeping a strong grounding in operations and optimisation.
10 years of coding experience
15 years of employment as a software developer
MBA Business Administration, MBA Business Administration at Quantic School of Business and TechnologyMPhil Engineering Management, MPhil Engineering Management at University of Cape TownMSc Financial Engineering, MSc Financial Engineering at WorldQuant UniversityPhD Computer Science, PhD Computer Science at North-West University / Noordwes-UniversiteitUniversity of South AfricaND Industrial Engineering, ND Industrial Engineering at Cape Peninsula University of Technology
English
Stackoverflow
540reputation
1.7mreached
4answers
5questions
Github Skills (42)
flask8
densenet8
springboard8
classifier8
webapp7
resnet7
keras7
api6
cloudant6
ggplot6
excel6
aggregate-functions6
greatest-n-per-group6
dataframe6
r6
Programming languages (2)
Github contributions (5)
reconstructive/reconstructive.github.io
Mar 2021 - Feb 2023
Contributions:45 commits, 47 pushes, 1 branch in 1 year 11 months
FraudML/Autoencoder-for-Fraud-Detection
Apr 2020 - Oct 2020
Contributions:33 commits, 30 pushes, 1 branch in 5 months
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