Remote Senior Data Scientist — Insurance Analytics Leader

Placements24; South Africa; Remote; ZAR 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Remote-friendly culture

Stock options

Home office stipend

Job summary

Placements24 is seeking a Senior Data Scientist to join a fully remote team. You will build advanced analytical models for insurance products, pricing, risk, and customer experience, using large datasets to derive actionable insights and communicate results to technical and non-technical stakeholders.

The ideal candidate has a strong background in statistical modeling, machine learning, and data mining, with practical insurance domain experience.

Qualifications

• PhD or Master’s in CS, Statistics, Mathematics, or related field.
• 5+ years hands-on data science, building and deploying production models.
• Strong Python or R skills with data science libraries.
• SQL proficiency and experience with large databases.
• Insurance/financial services industry experience is desirable.
• Excellent problem-solving and communication skills.

Responsibilities

• Design, develop, and deploy ML models for insurance analytics (fraud, churn, risk).
• Prepare and transform large datasets from multiple sources.
• Perform statistical analyses to identify trends and insights.
• Implement A/B testing to assess model performance.
• Collaborate with product, engineering, and business stakeholders.
• Communicate findings via visuals and presentations.
• Stay updated on new DS/AI advances and mentor juniors.

Skills

Statistical modeling

Machine learning

Data mining

Communication skills

Independent remote work

Education

PhD or Master’s in CS/Statistics/Math

5+ years data science experience

Tools

Python

R

scikit-learn

TensorFlow

PyTorch

Pandas

SQL

Job description

Placements24 is seeking a Senior Data Scientist to join a fully remote team. You will build advanced analytical models for insurance products, pricing, risk, and customer experience, using large datasets to derive actionable insights and communicate results to technical and non-technical stakeholders.

The ideal candidate has a strong background in statistical modeling, machine learning, and data mining, with practical insurance domain experience.