P&C Actuary and Portfolio Risk Manager

About Open Train

Open Train is the #1 platform for finding and building careers in AI training and data labeling. It connects skilled professionals with opportunities to help shape modern AI systems, build a credible work profile, and apply in minutes.

As an Open Train contractor, you will contribute specialized insurance expertise to projects that require careful reasoning, quantitative judgment, and clear communication.

AI training is the human side of building artificial intelligence. People with professional expertise create examples, write reference answers, and evaluate model responses so AI systems can reason more accurately and communicate more effectively.

This role focuses on expert text generation and response evaluation. Your actuarial judgment will help models understand insurance methods, assumptions, calculations, limitations, and business implications.

Open Train is recruiting P&C actuaries and portfolio risk professionals to develop high-quality insurance reasoning data for AI systems. You will design realistic pricing, reserving, forecasting, and portfolio-management scenarios, produce expert reference work, and evaluate model responses against actuarial standards.

The position is listed at the entry level, while the requirements call for at least two years of professional experience in P&C actuarial work, insurance pricing, reserving, catastrophe modeling, or portfolio risk management.

• Work type:
  Remote contractor and part-time
• Pay: $80 per hour after successful completion of onboarding
• Onboarding payment:
  Flat $800 upon successful completion
• Expected commitment:
  At least 20 hours per week, with 40 or more hours preferred
• Language:
  English
• Eligible locations:
  United States, Canada, United Kingdom, Australia, New Zealand, Ireland, Malta, the Netherlands, Sweden, Denmark, Norway, Finland, Germany, Austria, and Belgium

You will create realistic insurance scenarios and expert analyses covering both account-level and portfolio-level questions. You will also review AI-generated work and provide written feedback that improves model behavior.

Your work will require attention to mathematical accuracy, actuarial methodology, assumptions, data support, interpretation, and communication for both technical and nontechnical audiences.

• Design scenarios involving loss costs, rate indications, trend, development, credibility, segmentation, reserving, profitability, capital, catastrophe exposure, and portfolio concentration.
• Create pricing analyses, reserve reviews, portfolio diagnostics, assumption critiques, sensitivity analyses, and management recommendations.
• Write high-quality reference responses to experienced actuarial and portfolio-risk standards.
• Evaluate AI-generated responses for mathematical accuracy, assumption quality, methodology, interpretation, and communication.
• Identify calculation errors, unsupported assumptions, misuse of actuarial methods, and conclusions that are not supported by the data.
• Explain findings and provide written feedback that helps improve AI model behavior.

You should bring professional P&C actuarial or portfolio risk experience and the ability to apply quantitative analysis to insurance data. Strong written communication is essential because the work involves explaining technical methods, limitations, and business implications clearly.

You should be comfortable distinguishing account-level underwriting judgment from portfolio-level actuarial analysis and evaluating whether conclusions are supported by the available data.

• At least two years of professional experience in P&C actuarial work, insurance pricing, reserving, catastrophe modeling, or portfolio risk management.
• Experience analyzing insurance premium, exposure, claim, loss, or reserve data using spreadsheets or analytical tools.
• Ability to assess actuarial methods, assumptions, mathematical accuracy, and data-supported conclusions.
• Ability to distinguish account-level underwriting judgment from portfolio-level actuarial analysis.
• Strong quantitative reasoning, written communication, attention to detail, and spreadsheet proficiency.
• Experience with an analytical or statistical tool.

The following experience is valuable but not required: ACAS or FCAS credentials, active progress toward CAS credentials, and work across different insurance portfolio types or stakeholder groups.

• Personal, commercial, specialty, or reinsurance portfolios.
• Catastrophe or capital modeling.
• Predictive modeling or rate filings.
• Presenting results to underwriting, finance, claims, or executive stakeholders.
• SQL, R, Python, SAS, or actuarial modeling platforms.

AI training is a fast-growing area of technology work, and specialist contributors directly influence how advanced AI systems reason and respond. Your insurance expertise can help models handle complex quantitative and business questions more reliably.

Many AI training projects are remote and flexible, allowing…