Actuarial Business Analyst – Data Science and Machine Learning Lead at Badger Holdings (Pty) Ltd

• We’re on the hunt for an Actuarial Business Analyst who can lead a team of Data Scientists to build machine learning models that move the needle. You’ll be the translator, the strategist, and the impact-driver, making sure every model delivers measurable value and is understood from boardroom to operations floor.
• If you can bridge deep technical expertise with commercial impact and lead a high-performance analytics team, this is your seat at the table.

What You’ll Do

Lead & Inspire

• Manage, mentor, and grow a team of Data Scientists into a powerhouse of delivery.
• Build a culture where experimentation, collaboration, and results thrive.

Design & Deliver

• Oversee the creation, testing, and deployment of machine learning models that solve real business problems.
• Measure, quantify, and communicate the commercial impact of analytics solutions.
• Keep models relevant, accurate, and laser-focused on business goals.

Bridge Tech & Business

• Be the go-to liaison between data science and decision-makers.
• Translate complex analytics into plain, actionable English
• Ensure operational teams adopt and use model outputs effectively.

Drive Excellence

• Gather, refine, and document requirements for analytics projects.
• Push for best practices, smarter modelling approaches, and continuous process improvement.

Job Requirements

What You’ll Need to Bring

Essential:

• Degree or Honours in Actuarial Science.
• 7+ years’ experience in insurance or financial services (short-term insurance? Even better).
• Proven track record in building statistical/machine learning models.
• Skill in turning model outputs into business gold.
• Leadership experience in Data Science, Analytics, or Actuarial teams.
• Experience with claims modelling & survival analysis in insurance.
• BI tool mastery (Power BI, Qlik Sense, Tableau, etc.).
• Exceptional stakeholder engagement and communication skills.

Preferred:

• Hands-on skills in Python, R, SQL, and cloud platforms like Snowflake.
• Experience shaping both technical and business requirements.
• Strong grasp of data-driven decision frameworks.