Data Scientist

Old Mutual; Johannesburg; On-site; ZAR 900,000 - 1,200,000; Full time

Job summary

Old Mutual Insure in South Africa is hiring across generative AI, AI engineering, machine learning engineering and data science. Whether you build LLM-powered applications, productionise ML systems, or model risk and customer behaviour, you will play a critical role in turning data and AI into action.

Our core work today is generative AI and applied ML engineering — building, deploying and running intelligent systems in production — supported by a deep data science capability that keeps us

Qualifications

• 2+ years’ experience in AI/ML engineering, software engineering, data science, analytics or actuarial environments.
• Strong Python and SQL with solid backend fundamentals and data modelling.
• Cloud platforms (AWS, Azure, Databricks) and containerisation (Docker, Kubernetes).
• Experience building and evaluating ML models (supervised/unsupervised).
• Heads-on with LLM APIs and generative AI frameworks (LangChain, LlamaIndex).
• Experience with ML frameworks and deploying models to production.
• Understanding of AI governance, security and compliance in regulated settings.
• Growth mindset with real-world impact focus.
• Bonus: insurance or financial services experience, or data product development.

Responsibilities

• Build generative AI applications—LLM-powered assistants, RAG, and automation.
• Develop prompts, evaluation pipelines, guardrails and safety controls.
• Design and deploy ML pipelines and production inference services.
• Apply MLOps: CI/CD, feature stores, model registries, retraining, monitoring.
• Develop models for pricing, risk, claims and customer behaviour.
• Improve inference cost, latency and performance across AI/ML workloads.
• Create end-to-end solutions reshaping underwriting, claims, pricing, and engagement.
• Extract insights from data to guide business decisions.
• Participate in agile squads with actuaries and tech teams.
• Advance future-fit insurance architecture with AI and cloud-native tools.
• Communicate findings through visualisations and storytelling.

Skills

Python

SQL

Cloud platforms

Docker & Kubernetes

LLM APIs

ML Frameworks

MLOps

Data Wrangling

AI Governance

Agile

Education

Bachelor's degree in Data Science

Statistics

Computer Science

Actuarial Science

Engineering

Applied Mathematics

BCom: CS & Engineering

Tools

Databricks

Git

Docker

Kubernetes

LangChain

LlamaIndex

PyTorch

TensorFlow

Scikit-learn

APIs

Job description

Let's Write Africa's Story Together!

Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.

Job Description

Are you passionate about using data to fundamentally rethink how insurance works? Are you energized by the idea of designing the future model of insurance—one that’s fast, fair, predictive, and personal? At Old Mutual Insure, we’re building exactly that.

We are hiring across generative AI, AI engineering, machine learning engineering and data science. Whether you build LLM-powered applications, productionise ML systems, or model risk and customer behaviour, you will play a critical role in turning data and AI into action. Our core work today is generative AI and applied ML engineering — building, deploying and running intelligent systems in production — supported by a deep data science capability that keeps us future fit.

Responsibilities

• Building generative AI applications — LLM-powered assistants, RAG over enterprise content, agentic and workflow-automation solutions
• Engineering prompts, evaluation pipelines, guardrails and safety controls for AI systems in production
• Designing and deploying machine learning pipelines and production inference services, including predictive and generative models
• Applying MLOps practices — CI/CD for ML, feature stores, model registries, automated retraining, monitoring and drift detection
• Developing statistical and machine learning models for pricing, risk, claims and customer behaviour, and taking them to production
• Optimising inference cost, latency and performance across AI and ML workloads
• Engineering end-to-end solutions that reshape underwriting, claims, pricing, and customer engagement
• Extracting insights from customer, product, and operational data to inform and guide business decisions
• Participating in agile delivery squads and working closely with actuaries, product owners, and tech teams
• Contributing to the future-fit insurance architecture by innovating with AI, APIs, and cloud-native tools
• Communicating findings and ideas through impactful visualisations and storytelling

What We’re Looking For

• 2+ years’ experience in AI/ML engineering, software engineering, data science, analytics or actuarial environments (3+ years for engineering-focused profiles, 5+ for senior data science)
• Strong Python and SQL, with solid backend/software engineering fundamentals and data wrangling and modelling foundations
• Experience with cloud platforms (e.g. AWS, Azure, Databricks), containerisation (Docker, Kubernetes), APIs, CI/CD and Git
• Experience building and evaluating machine learning models (supervised and unsupervised)
• Hands‑on experience with LLM APIs and generative AI frameworks (e.g. LangChain, LlamaIndex), embeddings and vector databases
• Experience with ML frameworks such as Scikit-learn, PyTorch or TensorFlow, and taking models from prototype to production
• Understanding of AI evaluation, governance, security and compliance in a regulated environment
• A problem-solver with a growth mindset and hunger to apply their skills to real-world business impact
• Bonus: insurance or financial services experience, responsible AI, or data product development

Skills

• Applied Statistics & Probability
• Machine Learning (regression, classification, clustering)
• Feature Engineering & Model Evaluation
• Data & ML Engineering (pipelines, APIs, Docker, CI/CD, cloud)
• Effective Communication & Visual Storytelling
• Cross‑functional Collaboration & Agile Methodologies
• Generative AI & LLMs (prompt engineering, RAG, agents, evaluation)
• MLOps & Model Deployment (monitoring, drift detection, retraining)
• Responsible AI & Model Governance
• Software Engineering Practices (version control, testing, code quality)

Competencies

• Business Insight – Understands how data drives commercial outcomes
• Tech Curious – Keeps up with new ML tools, AI trends, and best practices
• Collaborates Effectively – Works fluidly across business and technical teams
• Drives Results – Delivers with discipline, quality, and impact
• Cultivates Innovation – Brings fresh ideas to complex challenges
• Manages Complexity – Makes sense of messy, ambiguous data environments
• Ensures Accountability – Follows through and learns from feedback
• Optimizes Processes – Simplifies, automates, and scales where possible
• Manages Multiple Priorities Under Pressure – Handles competing deadlines and tasks with resilience, structure, and delivery focus.

Education

• Bachelor’s degree in one of the following (or equivalent experience):
• Data Science
• Statistics
• Computer Science
• Actuarial Science
• Engineering
• Applied Mathematics

Skills

• Action Planning
• Business Requirements Analysis
• Computer Literacy
• Data Compilation
• Data Controls
• Data Management
• Executing Plans
• IT Architecture
• IT Network Security
• Policies & Procedures

Competencies

• Business Insight
• Collaborates
• Cultivates Innovation
• Drives Results
• Ensures Accountability
• Manages Ambiguity
• Manages Complexity
• Optimizes Work Processes

Education

• Bachelor of Commerce (BCom): Computer Science And Engineering (Required), NQF Level 7 - Degree, Advance Diploma or Postgraduate Certificate or equivalent

Closing Date

20 August 2026 , 23:59

The appointment will be made from the designated group in line with the Employment Equity Plan of Old Mutual South Africa and the specific business unit in question.

The Old Mutual Story!