Data Science Lead | George, Western Cape | On-site
Badger Holdings Pty Ltd · Western Cape
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Start free — we apply for you →What you'll do
As our Data Science Lead, you'll lead a team of three Data Scientists and one Machine Learning Engineer while driving strategic AI initiatives across the business.
You'll
- Lead the end-to-end delivery of machine learning and AI projects from business discovery through deployment and monitoring.
- Build, validate and deploy predictive models across customer lifetime value CLV, fraud detection, lapse prediction, pricing optimisation, claims prediction and customer segmentation.
- Work closely with stakeholders across underwriting, claims, finance and operations to identify high-value opportunities.
- Translate commercial challenges into scalable data science solutions.
- Ensure models are production-ready, explainable, governed and deliver measurable business value.
- Present insights and recommendations to senior leadership and executive stakeholders.
- Mentor, coach and develop the Data Science team while establishing technical best practices.
- Collaborate with Data Engineering, Analytics Engineering and ML Engineering to deliver robust AI solutions.
- Contribute to ARC's evolving AI ecosystem across Azure, GCP and modern cloud data platforms.
What we're looking for
- You'll thrive in this role if you combine technical excellence with strong leadership and commercial thinking.
Requirements
Qualifications
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or a related quantitative discipline.
- A postgraduate qualification in a relevant field is advantageous.
- Relevant cloud, AI or machine learning certifications Azure, Google Cloud, AWS, Databricks or Snowflake will be advantageous.
Essential experience
- 5+ years' experience in Data Science, Machine Learning or Artificial Intelligence.
- Previous experience leading or mentoring Data Science teams.
- Proven success delivering production machine learning models with measurable business impact.
- Strong Python and SQL skills.
- Experience across supervised, unsupervised and time-series modelling techniques.
- Experience owning the full machine learning lifecycle from problem definition to production deployment.
- Strong stakeholder engagement and business partnering skills.
- Experience presenting technical concepts to senior leadership and non-technical audiences.
- Knowledge of cloud platforms such as Azure, AWS or Google Cloud Platform GCP.
- Understanding of model governance, explainability and responsible AI.
Highly advantageous
- Insurance or Financial Services experience.
- Experience with fraud detection, customer propensity, churn or CLV modelling.
- MLOps and production deployment pipelines.
- Snowflake, dbt or modern cloud data platforms.
- Azure ML, Vertex AI, BigQuery ML or Databricks.
- Exposure to Generative AI, Large Language Models LLMs or AI Agent frameworks.
- Experience working within regulated environments POPIA, FAIS, TCF.