Data Scientist / Machine Learning Engineer
Location: Remote
Salary: Market related
Duration: 12 month contract
Build production-grade AI systems that power the future of digital banking.
Is this you?
You’re a hands-on Machine Learning Engineer who enjoys turning data science ideas into reliable, scalable systems. You’re comfortable working independently in a remote, global team, yet highly collaborative by nature. You care about clean code, robustness, and seeing models perform in the real world rather than living in notebooks.What you’ll be doing (and why you’ll enjoy it)
You’ll design, build, deploy, and maintain production ML and AI solutions supporting a digital-only bank. This includes use cases such as credit scoring, fraud detection, recommendation engines, and NLP-driven chatbots using modern GenAI techniques. You’ll operationalise end-to-end ML pipelines, expose models via APIs, deploy into secure on-premise environments, and monitor performance, drift, and reliability. You’ll also contribute to architecture decisions and work closely with data scientists, data engineers, DevOps, and domain teams.Where you’ll be doing it
Our client is a forward-thinking technology organisation delivering data and AI platforms for a large-scale digital banking initiative in Northern Africa. The environment is highly collaborative, engineering-led, and focused on modern, open-source and containerised technologies. You’ll be part of an international team shaping how trusted data products and AI capabilities are delivered in a regulated setting.What you’ll need
You’ll bring 4+ years’ experience in machine learning engineering or hybrid ML/software roles, strong Python skills, and hands-on experience deploying ML models into production. A solid understanding of data science workflows, feature engineering, and model validation is essential, along with experience in on-prem or hybrid environments. Exposure to GenAI, RAG pipelines, or financial services is highly advantageous.What you’ll get
A full-time contract with strong renewal prospects, the flexibility of remote work, exposure to enterprise GenAI initiatives, and the opportunity to influence AI/ML engineering standards on a high-impact banking projectHow to apply
For a confidential discussion please contact Judy Engelbrecht on (010) 065 1655 or send your CV to judy.engelbrecht@ttec.co.za – We appreciate that your CV might not be fully up to date. No problem, just send us what you have. We do respond to everyone! Just give us a few days to work through your application.Applicant Consent
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