Design insurance pricing, reserving, forecasting, and portfolio-risk scenarios for AI model training. Create actuarial analyses and reference answers, evaluate AI outputs for quantitative and methodological accuracy, identify unsupported assumptions and errors, and provide structured feedback. The role requires explaining actuarial methods and business implications to technical and nontechnical audiences while participating in calibration and onboarding sessions.
This role is for one of our clients
Compensation: $80 per hour
We are partnering with a leading AI lab to train frontier models on high-quality insurance reasoning data. We're hiring P&C Actuaries and Portfolio Risk Managers to design realistic pricing, reserving, forecasting, and portfolio-management scenarios, evaluate model outputs against established actuarial standards, and help shape how the next generation of AI reasons quantitatively about insurance risk.
We welcome pricing actuaries, reserving actuaries, portfolio analysts, catastrophe-risk professionals, and actuarial managers from carriers, reinsurers, MGAs, and consulting firms.
Requirements
What You'll Do
- Design realistic scenarios involving loss costs, rate indications, trend, development, credibility, segmentation, reserving, profitability, capital, catastrophe exposure, and portfolio concentration
- Create work products such as pricing analyses, reserve reviews, portfolio diagnostics, assumption critiques, sensitivity analyses, and management recommendations
- Write "golden" reference responses at experienced actuarial and portfolio-risk quality
- Grade AI-generated responses against structured rubrics for mathematical accuracy, assumption quality, methodology, interpretation, and communication
- Identify calculation errors, unsupported assumptions, misuse of actuarial methods, confusing correlation with causation, and recommendations not supported by the data
- Provide written feedback the research team uses to improve model behavior
- Participate in onboarding office hours and calibration sessions
You're a Good Fit If You
- Have 2+ years of professional experience in P&C actuarial work, insurance pricing, reserving, catastrophe modeling, or portfolio risk management
- Have performed quantitative analysis using insurance premium, exposure, claim, loss, or reserve data
- Understand the difference between account-level underwriting judgment and portfolio-level actuarial analysis
- Can explain methods, assumptions, limitations, and business implications clearly to technical and nontechnical audiences
- Demonstrate strong quantitative reasoning, excellent written communication, and high attention to detail
- Are proficient with spreadsheets and at least one analytical or statistical tool
Bonus Qualifications
- ACAS, FCAS, or active progress toward CAS credentials
- Experience with personal, commercial, specialty, or reinsurance portfolios
- Catastrophe modeling, capital modeling, predictive modeling, or rate-filing experience
- Proficiency with SQL, R, Python, SAS, or actuarial modeling platforms
- Experience presenting results to underwriting, finance, claims, or executive stakeholders
Role Highlights
- Minimum 20 hours per week (ideally 40+)
- Role starts immediately, applications reviewed on a rolling basis
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Manage enterprise customers after implementation by creating joint success plans, conducting executive business reviews and operational workshops, recommending workflow improvements, and helping customers maximize Samsara’s IoT platform. Collaborate cross-functionally with Sales, Support, Sales Engineering, and Product; mentor Customer Success and Support teams; resolve issues; and drive safety, efficiency, and sustainability outcomes. The role is remote in Canada and requires 25–40% customer travel.
Top Skills:
IotSaaSVehicle Telematics
.png)
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Leads ambiguous, high-impact revenue strategy initiatives, including sales forecasting, pipeline health, capacity planning, organizational sizing, partnership modeling, and commercial deal economics. Builds repeatable operating processes, analyzes complex data, and delivers executive-ready recommendations. Partners across Sales, Finance, Partnerships, Services, Data, and Systems, influencing outcomes without direct authority.
Top Skills:
ExcelGoogle SheetsSQL
eCommerce • Healthtech • Kids + Family • Retail • Social Media
Build and scale reliable Snowflake data pipelines, ML pipelines, monitoring systems, and AI-driven agentic tooling that automates pipeline generation, testing, and maintenance. The role partners with analysts, data scientists, product teams, and analytics engineers to deliver scalable end-to-end data infrastructure for Babylist’s e-commerce platform.
Top Skills:
Agentic WorkflowsAmazon Ec2Amazon EksAmazon S3Apache AirflowAWSAws LambdaDbtLlmsMachine Learning PipelinesMcp ServersPythonRagSnowflake
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.
