Senior Data Scientist: Revenue & Risk Analytics (Remote)

North American Search Group; United States; Remote; USD 130,000 - 160,000; Full time

Job summary

North American Search Group is seeking a Senior/Lead Data Scientist to work remotely across the United States. You will own revenue optimization initiatives, build data-driven narratives for client teams, and influence the product roadmap with validated analytics and ML-based insights.

The role requires strong Python or R skills, experience in risk modeling, and understanding of underwriting, pricing, capital modeling, and reinsurance.

Qualifications

• Strong data analysis and programming skills in Python or R.
• Experience in risk modeling, validation
• Understanding of insurance underwriting, pricing practices, capital modeling, and reinsurance.

Responsibilities

• Revenue optimization and risk mitigation: Own and identify innovative new strategies across the entire revenue waterfall to grow and recover revenue together with client-facing teams.
• Storytelling for client-facing teams: Build talk tracks and narratives for Revenue to continuously optimize and grow existing partnerships, backed by data insights from testing, Monte Carlo simulations, and/or ML models.
• Influence the product roadmap: Test optimization ideas, prove they work with data, and make the case to backend Product and Engineering teams to turn them into features that change how the company makes money.
• Data Infrastructure: Own, refine, and improve existing data pipelines to harness the power of data analytics, defining data structures, and leveraging advanced tracking methodologies to uncover revenue opportunities.
• Set the standard for the team in terms of analytical thinking and excellence.

Skills

Python

R

Job description

North American Search Group is seeking a Senior/Lead Data Scientist to work remotely across the United States. You will own revenue optimization initiatives, build data-driven narratives for client teams, and influence the product roadmap with validated analytics and ML-based insights.

The role requires strong Python or R skills, experience in risk modeling, and understanding of underwriting, pricing, capital modeling, and reinsurance.