Actuarial Business Analyst (Data Science & Machine Learning Focus) (George Onsite)

DataFin; Wes-Kaap; On-site; ZAR 600,000 - 900,000; Full time

Job summary

A leading insurance technology firm in South Africa is seeking an experienced Actuarial Business Analyst. You will lead a team of Data Scientists to implement Machine Learning models and translate complex insights for operational teams. The ideal candidate must have an Honours/Degree in Actuarial Science and at least 7 years of experience in the insurance sector, along with proficiency in BI tools. This role offers a unique opportunity to bridge Data Science and business.

Qualifications

• 7 years' experience in the Insurance or Financial Services sector.
• Proven experience in developing statistical and/or Machine Learning models.
• Experience with Claims Modelling and Survival Analysis/Modelling.

Responsibilities

• Lead and mentor a team of Data Scientists.
• Oversee the development and deployment of Machine Learning models.
• Serve as liaison between Data Science and business stakeholders.

Skills

Leadership

Data Science

Stakeholder Engagement

Education

Degree or Honours in Actuarial Science

Tools

Power BI

Qlik Sense

Tableau

Job description

Environment

OUR client is redefining how insurance and technology work together and is looking for an experienced Actuarial Business Analyst with a strong focus on leading a team of Data Scientists to design, develop, and implement Machine Learning models. The role involves evaluating and quantifying the business impact of these models, translating complex analytical outputs into clear, actionable insights, and ensuring operational teams fully understand and leverage the results. You will act as the key bridge between Data Science and business, driving measurable value through advanced analytics. The successful incumbent must possess an Honours/Degree in Actuarial Science with 7 years’ experience in the Insurance or Financial Services sector (preferably short-term insurance) including proven experience in developing statistical and/or Machine Learning models. You also require proficiency in BI tools such as Power BI, Qlik Sense, Tableau, or similar platforms.

Duties

• Leadership & Team Management: Lead and mentor a team of Data Scientists to deliver impactful Machine Learning solutions.
• Foster a culture of innovation, collaboration, and continuous improvement.

• Model Development & Evaluation: Oversee the development, testing, and deployment of Machine Learning models.
• Evaluate and quantify the business impact of analytical solutions.
• Ensure models are accurate, relevant, and fit-for-purpose.

• Stakeholder Engagement: Serve as the primary liaison between the Data Science team and business stakeholders.
• Translate technical concepts into actionable recommendations for both technical and non-technical audiences.
• Communicate insights effectively, ensuring operational adoption of model outputs.

• Project & Requirements Management: Gather, define, and document business and technical requirements for Data Science projects.
• Ensure projects align with strategic business objectives and deliver measurable outcomes.

• Best Practice & Process Improvement: Champion best practices in analytics, modelling, and business integration.
• Identify opportunities to improve modelling approaches and operational use of analytics.

Requirements

Qualifications

• Degree or Honours in Actuarial Science.

Experience / Skills

• Minimum 7 years’ experience in the Insurance or Financial Services sector (preferably short-term insurance).
• Proven experience in developing statistical and/or Machine Learning models.
• Demonstrated ability to assess and articulate the business impact of Machine Learning models.
• Previous leadership experience within Data Science, Analytics, or Actuarial teams.
• Experience with Claims Modelling and Survival Analysis/Modelling in the Insurance industry.
• Proficiency in BI tools such as Power BI, Qlik Sense, Tableau, or similar platforms.

Preferred / Advantageous

• Familiarity with Python, R, SQL, and cloud data platforms such as Snowflake.
• Understanding of data-driven decision-making frameworks.
• Experience in capturing and managing both business and technical requirements.

Attributes

• Ability to interpret complex model outputs and translate them into clear business recommendations.
• Strong interpersonal, communication, and stakeholder engagement skills.