Remote Insurance Data Scientist — Predictive Analytics & Impact

Placements24; Bloemfontein; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Remote-friendly culture

Home office stipend

Flexible hours

Job summary

Placements24 is seeking an experienced Insurance Data Scientist for a fully remote role in South Africa. You will leverage large datasets, build predictive models, and contribute to pricing, risk assessment, and fraud detection across underwriting, claims, and marketing teams.

The ideal candidate has a master's or PhD in a quantitative field, 5+ years in data science within insurance or financial services, strong Python or R skills, SQL, and experience with scikit-learn, TensorFlow or PyTorch.

Qualifications

• Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 5 years hands-on data science experience in insurance or financial services.
• Proficiency in Python or R with relevant libraries (scikit-learn, TensorFlow, PyTorch, pandas).
• Strong SQL skills and experience with large databases.

Responsibilities

• Develop and implement advanced statistical models and ML algorithms for predicting customer behavior, fraud, pricing, and risk.
• Analyze large datasets to extract actionable insights and trends.
• Design and execute A/B tests and experiments to evaluate strategies and products.
• Collaborate with underwriting, claims, and marketing to translate business challenges into data science projects.
• Communicate findings clearly to technical and non-technical audiences with visualizations.

Skills

Python

R

SQL

Statistical modeling

Machine learning

Communication

Education

Master's or PhD in Data Science/Statistics/CS/Math or related

Tools

scikit-learn

TensorFlow

PyTorch

Pandas

Spark

Hadoop

Job description

Placements24 is seeking an experienced Insurance Data Scientist for a fully remote role in South Africa. You will leverage large datasets, build predictive models, and contribute to pricing, risk assessment, and fraud detection across underwriting, claims, and marketing teams.

The ideal candidate has a master's or PhD in a quantitative field, 5+ years in data science within insurance or financial services, strong Python or R skills, SQL, and experience with scikit-learn, TensorFlow or PyTorch.