Remote Insurance Risk Strategist

Placements24; Upington; Hybrid; ZAR 360,000 - 480,000; Full time

Benefits offered by this job

Competitive salary and bonus structure

Comprehensive health, dental, and退休/养老

Significant professional development

Fully remote work arrangement

Autonomy and work-life balance

Job summary

Placements24 is seeking a Remote Insurance Risk Analyst to join a proactive risk management team. Work entirely remotely, identifying, assessing and mitigating risks across the insurance portfolio with data analysis, model development and strategic recommendations.

Ideal candidates will have strong quantitative skills, experience in statistical modeling, and proficiency in R, Python and SQL, plus knowledge of insurance products and regulatory frameworks.

Qualifications

• Proven experience as a Risk Analyst in insurance or financial services.
• Strong quantitative and analytical skills with statistical modeling.
• Proficiency in R, Python, SQL and data visualization.
• Degree in Finance, Economics, Statistics, Mathematics, or related field.

Responsibilities

• Analyze insurance data to quantify financial and operational risks.
• Develop risk models and methodologies to forecast losses.
• Monitor KRIs and report emerging risks to senior management.
• Collaborate with underwriting, actuarial, and finance teams on mitigations.
• Prepare comprehensive risk assessment reports and present findings to senior management.
• Ensure compliance with regulatory requirements and internal policies.

Skills

Quantitative analysis

Statistical modeling

Data analysis

R

Python

SQL

Insurance knowledge

Regulatory understanding

Remote collaboration

Education

Finance/Economics/Statistics/Math degree

Tools

R

Python

SQL

Tableau

Job description

Placements24 is seeking a Remote Insurance Risk Analyst to join a proactive risk management team. Work entirely remotely, identifying, assessing and mitigating risks across the insurance portfolio with data analysis, model development and strategic recommendations.

Ideal candidates will have strong quantitative skills, experience in statistical modeling, and proficiency in R, Python and SQL, plus knowledge of insurance products and regulatory frameworks.