Claims Analytics Data Analyst - Remote-Eligible

Old Mutual; Mahikeng; On-site; ZAR 350,000 - 500,000; Full time

Benefits offered by this job

Medical aid

Retirement plan

Paid leave

Wellness initiatives

Flexible working

Tuition assistance

Job summary

Old Mutual in Mafikeng, South Africa, is seeking an Insurance Claims Data Analyst to turn raw claims data into actionable insights. You will report to the Claims Analytics Manager and collaborate with actuarial, underwriting, and IT teams on predictive models, trend monitoring, and fraud detection.

The role supports the company’s digital transformation and data-driven decision making, offering exposure to dashboards, data pipelines, and governance.

Qualifications

• Bachelor’s degree in Finance, Business, Economics, Statistics, CS or related field.
• 3–5 years of professional data analysis experience.
• Experience in insurance or financial services preferred.
• Proficiency with SQL and Python or R.

Responsibilities

• Collect, cleanse, and validate large volumes of claims data.
• Develop predictive models to forecast claim frequency and severity.
• Identify patterns indicating fraud and suggest mitigations.
• Create dashboards and reports for senior management.
• Collaborate with IT to automate data pipelines and improve data access.
• Support pricing and reserving with data-driven insights.
• Stay updated on analytics technologies.

Skills

SQL

Python

R

Statistical modeling

Machine learning

Data visualization

Communication

Education

Bachelor's degree in Finance/Business/Economics/Statistics/CS

Tools

Power BI

Tableau

Job description

Old Mutual in Mafikeng, South Africa, is seeking an Insurance Claims Data Analyst to turn raw claims data into actionable insights. You will report to the Claims Analytics Manager and collaborate with actuarial, underwriting, and IT teams on predictive models, trend monitoring, and fraud detection.

The role supports the company’s digital transformation and data-driven decision making, offering exposure to dashboards, data pipelines, and governance.