Data Scientist | On-site | George, Western Cape

Job description

Data Scientist | On-site | George, Western Cape

Turn data into decisions that actually matter.

You won’t just build models here, you’ll shape how the business thinks, predicts, and grows. This is a role where your work directly influences strategy, pricing, and customer outcomes, especially at the intersection of data science and actuarial thinking.

About the role

You’ll take ownership of the full machine learning lifecycle; from raw data to deployed, production-ready models that deliver real business value. Working closely with actuarial, data, and business teams, you’ll translate complex problems into practical, scalable solutions.

Your day-to-day will include:

• Preparing and transforming data for machine learning (cleaning, feature engineering, optimisation)

• Conducting exploratory analysis to uncover trends and guide model design

• Building, testing, and deploying machine learning models aligned to business needs

• Collaborating with actuarial teams to align assumptions and modelling approaches

• Validating models and ensuring performance, accuracy, and reliability

• Monitoring live models for drift and performance degradation

• Maintaining, retraining, and improving models over time

• Creating clear documentation for models, pipelines, and processes

• Developing dashboards and reporting tools to track performance and KPIs

• Communicating insights and recommendations to both technical and non-technical stakeholders

About you

You’re someone who enjoys solving real problems and not just building models for the sake of it. You’re curious about the “why” behind the data and motivated by the impact your work can have.

Requirements:

• A degree (Honours preferred) in Data Science, Actuarial Science, Statistics, Mathematics, or a related field

• 3+ years’ experience in data science or machine learning roles

• Strong Python and R skills, with proven experience building and deploying models

• Solid experience across the full ML lifecycle (data → model → deployment)

• Hands-on experience with statistical modelling, machine learning, and time series forecasting

• The ability to translate technical outputs into clear business value

• Strong communication and stakeholder engagement skills, particularly with actuarial teams

• A proactive, energetic mindset and a genuine passion for data and innovation

Nice to have:

• Experience in insurance (especially short-term insurance)

• Exposure to CLTV modelling, claims modelling, survival analysis, or actuarial-related work

• Experience with dbt, Snowflake, GCP, or similar cloud platforms

• Familiarity with MLOps practices and machine learning platforms

• Experience with BI tools (Power BI, Tableau, Looker, Qlik, etc.)

Why join us

This is more than a technical role; it’s an opportunity to influence decisions at a strategic level. You’ll work in a collaborative, forward-thinking environment where data is valued, experimentation is encouraged, and your ideas can make a tangible difference.

Expect:

• Meaningful, high-impact work

• Strong collaboration between data, actuarial, and business teams

• A culture that values curiosity, ownership, and innovation

• Opportunities to grow your technical and business skillset

Ready to make an impact?

If you’re excited about turning data into real-world outcomes and want to work where your models actually matter, we’d love to hear from you.

Posted on 04 May 12:16, Closing date 2 Jun