Jobs at Badger Holdings (Pty) Ltd

Position Responsibilities and Accountabilities

• Develop pricing models using actuarial software to improve accuracy of pricing models.
• Conduct in-depth profitability assessments across key business verticals.
• Develop practical pricing strategies.
• Review personal lines insurance product designs.
• Assist in monitoring claims trends and experience analysis to support business strategy.

Requirements

• Actuarial degree.
• Completion of Part A1: Foundational technical and A2: Intermediate Technical Actuarial exam series and Part A3: Actuarial Risk Management.
• 5+ years of actuarial experience in non-life insurance, with a focus on pricing.
• Strong technical skills, with proficiency in working with actuarial software.
• Excellent analytical, problem-solving, and communication skills.
• Ability to collaborate with cross-functional teams and present insights to both technical and non-technical stakeholders.
• A proactive mindset, with a passion for using data and analytics to drive business impact. 

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What You’ll Be Doing

• Build and maintain strong relationships with motor dealerships
• Act as the primary point of contact for your dealer portfolio
• Drive sales through consistent engagement (calls, follow-ups, and support)
• Identify opportunities to grow and strengthen accounts
• Resolve queries efficiently and ensure a high level of partner satisfaction
• Keep accurate records and actively manage your pipeline

Requirements

What We’re Looking For

• Matric (essential)
• Strong communication and relationship-building skills
• A proactive, results-driven mindset
• Ability to manage multiple accounts and priorities effectively
• Resilience and a strong sense of ownership
• Previous experience in sales, account management, or customer service (motor industry advantageous)
• Comfortable using CRM systems and Microsoft Office

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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).