Lead Insurance Data Scientist

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

About the Role

Our client, a pioneering force in the insurance technology space, is actively seeking a Lead Insurance Data Scientist to spearhead their advanced analytics initiatives. This pivotal role is based in the vibrant hub of Sandton, Gauteng , offering a strategic blend of in-office collaboration and remote flexibility. You will be instrumental in leveraging vast datasets to drive business insights, enhance risk modeling, optimize pricing strategies, and develop predictive analytics solutions. The ideal candidate possesses a deep technical expertise in data science, machine learning, and statistical modeling, combined with a strong understanding of the insurance domain. You will lead a team of talented data scientists, mentor junior members, and collaborate with key stakeholders across the organization to translate complex data findings into actionable business strategies. This is an opportunity to make a significant impact on how our client understands and interacts with risk.

Key Responsibilities

Lead the design, development, and implementation of advanced analytical models and machine learning algorithms for insurance applications (e.g., fraud detection, risk segmentation, customer lifetime value prediction). Extract, clean, and transform large, complex datasets from various sources, ensuring data integrity and quality. Develop and maintain data pipelines and analytical infrastructure to support ongoing data science projects. Interpret model results and translate complex findings into clear, concise recommendations for business stakeholders. Mentor and guide junior data scientists, fostering a collaborative and innovative team environment. Collaborate with product, underwriting, and claims teams to identify opportunities for data-driven improvements. Stay abreast of the latest advancements in data science, machine learning, and AI, and evaluate their potential application within the insurance industry. Present findings and insights to executive leadership and cross-functional teams.

Requirements

A Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field. A minimum of 7 years of experience in data science, with at least 3 years in a lead or management role. Extensive experience in building and deploying machine learning models (e.g., regression, classification, clustering, time series forecasting). Proficiency in programming languages such as Python or R, and expertise in SQL. Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP). Deep understanding of statistical modeling, experimental design, and hypothesis testing. Strong domain knowledge of the insurance industry, including underwriting, claims, and pricing. Excellent communication and leadership skills, with the ability to influence stakeholders at all levels.

Benefits

Our client offers a highly competitive salary, significant bonus potential, and a comprehensive benefits package including medical aid, a provident fund, and life assurance. Professional development is strongly encouraged, with access to training, conferences, and further education support. The hybrid work model provides flexibility to balance office and remote work. Employees have access to cutting-edge technology and tools, and the opportunity to work on challenging and impactful projects. Join a forward-thinking company culture that values innovation, collaboration, and employee well-being. Enjoy a stimulating work environment with ample opportunities for career growth.