Head of Insurance Data Science & Predictive Analytics

Placements24; Sandton; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Medical aid

Provident fund

Life assurance

Hybrid work model

Professional development

Job summary

Placements24 in Sandton, Gauteng, is seeking a Lead Insurance Data Scientist to drive advanced analytics initiatives. You will guide a team of data scientists, mentor juniors, and collaborate with product, underwriting, and claims teams to translate data into actionable business strategies.

The role focuses on risk modeling, pricing optimization, fraud detection, and customer lifetime value, leveraging Python/R, SQL, and big data tools in a hybrid work setup with remote flexibility.

Qualifications

• Master's or PhD in a quantitative field as required.
• Strong experience in data science and ML with leadership.
• Experience building and deploying ML models and data pipelines.

Responsibilities

• Lead design, development, and deployment of analytical models and ML algorithms for insurance applications.
• Extract, clean, and transform large datasets from diverse sources.
• Develop data pipelines and analytical infrastructure to support projects.
• Interpret results and present concise recommendations to stakeholders.
• Mentor junior data scientists and collaborate with cross-functional teams.
• Stay updated on advances in data science and AI for insurance.

Skills

Data science

Machine learning

Statistical modeling

Leadership

Stakeholder communication

Python/R

Education

Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, or related field

Tools

Python

R

SQL

Spark

Hadoop

AWS

Azure

GCP

Job description

Placements24 in Sandton, Gauteng, is seeking a Lead Insurance Data Scientist to drive advanced analytics initiatives. You will guide a team of data scientists, mentor juniors, and collaborate with product, underwriting, and claims teams to translate data into actionable business strategies.

The role focuses on risk modeling, pricing optimization, fraud detection, and customer lifetime value, leveraging Python/R, SQL, and big data tools in a hybrid work setup with remote flexibility.