Actuarial Business Analyst

Gap Consulting; George; On-site; ZAR 300 000 - 400 000; Full time

Job summary

An actuarial consulting firm in Western Cape is seeking an Actuarial Business Analyst to lead a team of Data Scientists. This role demands a strong background in actuarial methodologies alongside machine learning expertise, applied within the insurance or financial services sector. Candidates should possess a relevant degree and extensive experience in developing and deploying actuarial models for real-world applications. The position offers a negotiable basic salary along with incentives and benefits.

Benefits

Negotiable Basic Salary

Incentives

Benefits

Qualifications

• 7+ years' experience in the insurance or financial services industry.
• Proven expertise in building and deploying actuarial models.
• Strong experience in claims modelling and predictive analytics.

Responsibilities

• Lead a team of Data Scientists to deliver high-impact solutions.
• Operate and oversee the design and deployment of actuarial models.
• Act as the point of contact between data scientists and business stakeholders.

Skills

Actuarial techniques and methodologies

Machine learning

Leadership and mentoring

Communication skills

BI tools proficiency

Education

Degree or Honours in Actuarial Science

Tools

Python

R

SQL

Power BI

Tableau

Snowflake

AWS

Azure

Job description

SUMMARY

#SHIFTINTOHIGHCAREER by joining a Company that seeks the expertise of a Actuarial Business Analyst to manage a team of Data Scientists

POSITION INFO: Minimum Requirements

Essential

• Degree or Honours in Actuarial Science with a solid grounding in actuarial techniques and methodologies (e.g., risk modelling, claims prediction, survival analysis)
• 7+ years’ experience in the insurance or financial services industry, with a focus on actuarial analysis and the application of machine learning to solve actuarial problems
• Proven expertise in building and deploying actuarial models (pricing, reserves, claims forecasting) combined with machine learning techniques to enhance decision‑making
• Strong experience in claims modelling , survival analysis , and the application of predictive analytics to real‑world actuarial problems
• Leadership experience in managing or mentoring a team of actuarial professionals and data scientists to deliver complex analytics solutions
• Proficiency in BI tools (e.g., Power BI, Tableau, Qlik Sense) for translating model outputs into business‑friendly visualisations
• Excellent communication skills with the ability to convey complex technical findings in clear, actionable terms to non-technical stakeholders

Preferred

• Hands‑on experience with Python , R , SQL , and cloud platforms (e.g., Snowflake , AWS , or Azure ) for model development and deployment
• Experience working with large datasets and building scalable data pipelines to support actuarial and machine learning models
• Ability to shape and prioritise both technical and business requirements , balancing actuarial rigor with business acumen
• Strong understanding of data‑driven decision‑making frameworks, especially in actuarial and insurance contexts

Expectations

Direct & Cultivate

• Lead, mentor, and develop a team of Data Scientists to deliver high‑impact solutions using both actuarial methodologies and advanced machine learning techniques
• Cultivate a collaborative, high‑performance culture that encourages innovative problem‑solving and data‑driven decision‑making
• Ensure team members have the skills, resources, and support to push the boundaries of what's possible in actuarial and data science modelling

Design & Deliver

• Oversee the design, testing, and deployment of actuarial models (including pricing, claims reserving, and survival models) alongside machine learning models to solve critical business problems
• Combine actuarial science principles with advanced statistical modelling and machine learning algorithms to create highly effective, actionable solutions
• Measure, track, and communicate the commercial impact of models, ensuring clear business outcomes from every project
• Continuously evaluate and refine model accuracy, relevance, and alignment with shifting business priorities

Integrate Tech & Operations

• Act as the critical point of contact between the data scientists , and business stakeholders , ensuring alignment of business goals with technical deliverables
• Translate complex actuarial and machine learning concepts into clear, actionable insights for senior leadership, ensuring data‑driven decisions are well understood across the organization
• Lead the integration of actuarial model outputs into the day‑to‑day operations, driving operational change and ensuring model adoption at all levels of the business

Enhance Performance

• Gather and document detailed requirements for actuarial analytics projects, ensuring both technical and business needs are understood and addressed
• Promote the use of best practices in actuarial modelling, data science techniques, and machine learning deployments , striving for continuous improvement and innovation
• Identify and implement opportunities for process improvements, ensuring the models are optimised and the business is maximising the value of data

Salary Structure

• Negotiable Basic Salary
• Incentives
• Benefits