Data Science Lead (AI/ Software Development)

Morton Moore Pty Ltd; George; On-site; ZAR 837,000 - 949,000; Full time

Benefits offered by this job

Player-coach leadership

On-site role

Cloud-native data stack

Job summary

Morton Moore Pty Ltd in George seeks a Data Science Lead to drive its AI/ML capability. You will be a hands-on leader, mentoring a growing team while remaining close to modelling work and business outcomes.

The role covers end-to-end model lifecycle, governance, and modern cloud-native deployments on a permanent, on-site basis in George. Strong Python/SQL and cloud experience are essential.

Qualifications

• Minimum five years in data science or ML with senior/lead experience.
• Delivery of production ML models with measurable business impact.
• Strong Python and SQL skills; familiarity with data warehousing.
• Experience with cloud platforms like Azure, GCP or AWS.
• Hands-on with supervised, unsupervised and time-series modelling.

Responsibilities

• Lead design, development and deployment of ML models delivering commercial value.
• Own model lifecycle from discovery to production monitoring and retraining.
• Run discovery sessions to scope opportunities and define success metrics.
• Mentor data scientists while staying hands-on and hands-on with modelling.
• Advise on governance, validation, and regulatory compliance.

Skills

Python

SQL

Data Warehousing

Modeling: time-series

Supervised learning

Unsupervised learning

MLOps

Stakeholder engagement

Leadership

Tools

Snowflake

dbt

Databricks

Azure ML

Vertex AI

BigQuery ML

Job description

Overview

Our client, a well-established insurance and financial services group based in George, is seeking an experienced Data Science Lead to build and drive its AI and machine learning capability. This is a hands-on leadership role in a young, ambitious data organisation where the successful candidate will remain personally close to the modelling work while mentoring a growing team. The role is permanent and based on site in George.

Key Responsibilities

• Lead the design, development and production deployment of machine learning models that deliver measurable commercial value.
• Own the full model lifecycle end to end, from initial business requirement and discovery through to production monitoring and retraining.
• Run business discovery sessions with stakeholders to scope opportunities, define success measures and prioritise the AI delivery roadmap.
• Build and maintain supervised, unsupervised and time-series models across use cases such as customer lifetime value, propensity, churn and fraud detection.
• Partner with Data Engineering and Analytics Engineering teams to ensure robust, well-governed data pipelines supporting model development.
• Set and enforce technical standards for model quality, validation, documentation and peer review.
• Implement MLOps practices and production deployment pipelines on a modern cloud-native stack.
• Ensure model governance, explainability and compliance with regulatory expectations, including POPIA, FAIS and Treating Customers Fairly principles.
• Present model outputs, insights and recommendations to executive and non-technical business audiences in clear commercial language.
• Mentor and develop data scientists through pairing, code review and structured coaching while remaining personally hands-on.
• Shape the broader AI strategy in partnership with senior leadership and contribute to capability planning as the team scales.
• Evaluate and introduce relevant innovations, including large language models, generative AI and agent frameworks, where they create practical business value.
• Monitor deployed models in production and report on performance, drift and realised business impact.

Requirements

• At least five years' experience in data science or machine learning, including a minimum of two years in a senior or lead capacity.
• Proven track record of personally delivering production machine learning models with measurable business impact.
• Strong Python and SQL skills, with familiarity in modern data warehousing.
• Hands-on experience with supervised, unsupervised and time-series modelling techniques.
• Experience owning the full model lifecycle from business requirement through to production.
• Experience with cloud data platforms such as Azure, GCP or AWS.
• Strong business engagement and stakeholder communication skills, including presenting to executive committees.
• Experience leading or mentoring data science teams while remaining technically hands-on.
• Working awareness of model governance, explainability and regulatory requirements in a South African financial services context.
• Advantageous: insurance or financial services domain exposure, CLV, propensity, fraud or churn modelling, MLOps pipelines, Snowflake, dbt, Databricks, Azure ML, Vertex AI, BigQuery ML or generative AI frameworks.

Benefits and Compensation

• Our client is offering a salary of R 75 000 to R 85 000 per month, depending on experience and qualifications.
• A genuine player-coach leadership opportunity where you lead a team and stay in the work.
• Full ownership of AI initiatives that directly influence how the business grows, prices and retains customers.
• The opportunity to shape the AI strategy and delivery roadmap alongside senior leadership.
• Work with a modern, cloud-native data stack including Azure, Snowflake, Python, dbt and GCP.
• Scope to build a team culture and technical standard that becomes the benchmark across the group.
• Clear growth path into a broader AI leadership role as the capability and team scale.