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Actuarial Machine Learning Jobs (NOW HIRING)

Weekday AI

Risk & Actuarial AI Expert

$100 - $120/hr

This role sits at the intersection of actuarial science, risk management, and advanced analytics ... Enhancing traditional modeling approaches using machine learning techniques to improve prediction ...

Aon Corporation

Actuarial Director

Bloomington, MN · On-site

$150K - $180K/yr

Knowledgeable on pricing strategies using predictive analytics, actuarial techniques, and machine learning. * Build and refine pricing models to improve risk segmentation, profitability, and ...

Aon Corporation

Actuarial Director

Chicago, IL · On-site

$150K - $180K/yr

Knowledgeable on pricing strategies using predictive analytics, actuarial techniques, and machine learning. * Build and refine pricing models to improve risk segmentation, profitability, and ...

Aon Corporation

Actuarial Director

New York, NY

$150K - $180K/yr

Knowledgeable on pricing strategies using predictive analytics, actuarial techniques, and machine learning. * Build and refine pricing models to improve risk segmentation, profitability, and ...

Aon Corporation

Actuarial Director

Chicago, IL · On-site

$150K - $180K/yr

Knowledgeable on pricing strategies using predictive analytics, actuarial techniques, and machine learning. * Build and refine pricing models to improve risk segmentation, profitability, and ...

Bamboo Insurance

Actuarial Associate

Midvale, UT · On-site

$130K/yr

Experience with predictive modeling and advanced analytics techniques, including machine learning * Excellent communication skills to convey complex actuarial concepts to non-actuarial stakeholders.

Allstate

P&C Actuary Director - Reserving

Chicago, IL · On-site

Working proficiency with AI, machine learning, and generative AI as applied to reserving and broader actuarial work - including automated assumption selection and LLM-assisted documentation, analysis ...

Allstate

P&C Actuary Director - Reserving

Chicago, IL · On-site

Working proficiency with AI, machine learning, and generative AI as applied to reserving and broader actuarial work - including automated assumption selection and LLM-assisted documentation, analysis ...

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Actuarial Machine Learning information

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$22K

$93.5K

$154K

How much do actuarial machine learning jobs pay per year?

As of Sep 11, 2026, the average yearly pay for actuarial machine learning in the United States is $93,525.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $109,500.00 per year, depending on experience, location, and employer.

What is actuarial machine learning?

Actuarial machine learning is the application of machine learning techniques to traditional actuarial tasks, such as risk assessment, pricing, and forecasting in the insurance and financial industries. Actuaries use these advanced algorithms to analyze large datasets, identify patterns, and make more accurate predictions about future events. By leveraging machine learning, actuaries can enhance decision-making, improve efficiency, and uncover insights that may not be evident through traditional statistical methods.

What are the key skills and qualifications needed to thrive as an actuarial machine learning professional?

To thrive in Actuarial Machine Learning, you need a solid foundation in actuarial science, statistics, and advanced mathematics, typically supported by progress toward actuarial credentials and a relevant quantitative degree. Proficiency in programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or Scikit-learn), and familiarity with actuarial software are often required. Strong problem-solving skills, analytical thinking, and the ability to communicate complex findings clearly are standout soft skills in this field. These competencies enable professionals to design effective predictive models, translate data-driven insights into business value, and support risk management decisions in the insurance and finance sectors.

How do actuarial machine learning professionals typically collaborate with other departments within an organization?

Actuarial Machine Learning professionals frequently work closely with teams such as underwriting, claims, IT, and data engineering. They translate complex analytical findings into actionable insights for business leaders, participate in cross-functional meetings to align predictive models with business objectives, and often partner with software engineers to deploy machine learning models into production. Successful collaboration requires clear communication, adaptability, and a solid understanding of both actuarial principles and advanced analytics techniques. This team-based approach helps ensure that machine learning solutions are both technically sound and aligned with organizational goals.

What is the difference between Actuarial Machine Learning vs Actuarial Analyst?

AspectActuarial Machine LearningActuarial Analyst
Required credentialsActuarial exams, data science skillsActuarial exams, basic statistical knowledge
Work environmentData science teams, tech-focused projectsInsurance companies, risk assessment teams
Industry usageAdvanced modeling, predictive analyticsPricing, reserving, reporting

While both roles involve actuarial principles, Actuarial Machine Learning focuses on applying machine learning techniques to large datasets for predictive modeling, often requiring data science skills. Actuarial Analysts primarily perform traditional actuarial tasks like pricing and reserving using statistical methods. The roles differ in technical complexity and focus but share foundational actuarial credentials.

What cities are hiring for Actuarial Machine Learning jobs?

Cities with the most Actuarial Machine Learning job openings:

What other helpful pages are available for Actuarial Machine Learning?

Other pages related to Actuarial Machine Learning:

Infographic showing various Actuarial Machine Learning job openings in the United States as of September 2026, with employment types broken down into 20% Internship, and 80% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $93,525 per year, or $45 per hour.

Risk & Actuarial AI Expert

Remote

Weekday AI
See more jobs at Weekday AIexternal

$100 - $120/hr

Part-time

Re-posted 23 days ago

Job description

This role is for one of our clients
Compensation: $100-$120 per hour (20 hours per week commitment)
Job Type: Part-time / Contract
Location: US, UK, Canada, France, Portugal (remote)
We are seeking a highly analytical and forward-thinking Risk & Actuarial AI Expert to join our growing team. This role sits at the intersection of actuarial science, risk management, and advanced analytics, leveraging artificial intelligence to enhance decision-making across insurance and risk portfolios. The ideal candidate will bring a strong foundation in actuarial principles combined with hands-on experience in data science, enabling the transformation of complex risk data into actionable insights.
Requirements
Key Responsibilities:
You will play a central role in evaluating and optimizing portfolio performance through detailed loss ratio and combined ratio analysis. This includes monitoring trends, identifying deviations, and providing recommendations to improve underwriting profitability. A deep understanding of claims behavior, pricing adequacy, and expense structures will be critical to success in this area.
In addition, you will conduct comprehensive portfolio risk assessments, using statistical models and AI-driven techniques to evaluate exposure across various lines of business. This involves identifying risk concentrations, assessing diversification, and supporting strategic decisions related to risk selection and capital allocation. You will collaborate closely with underwriting, finance, and product teams to ensure alignment between risk appetite and business objectives.
A significant part of the role will focus on catastrophe modeling and exposure management. You will work with catastrophe models and geospatial data to assess potential losses from natural disasters and extreme events. Enhancing traditional modeling approaches using machine learning techniques to improve prediction accuracy and scenario analysis will be a key expectation. You will also contribute to stress testing, scenario planning, and regulatory reporting requirements.
AI & Analytics Integration:
The role requires leveraging modern AI/ML techniques to automate actuarial workflows, improve predictive modeling, and uncover hidden patterns in large datasets. You will design and implement models that enhance pricing, reserving, and risk selection processes. Experience with tools such as Python, R, and cloud-based analytics platforms will be valuable.
Qualifications & Skills:
  • Bachelor's or Master's degree in Actuarial Science, Mathematics, Statistics, Data Science, or a related field
  • Progress toward actuarial certification (e.g., IFoA, SOA, or equivalent) preferred
  • 2-8 years of experience in actuarial analysis, risk management, or insurance analytics
  • Strong expertise in loss ratio and combined ratio analysis
  • Proven experience in portfolio risk assessment and risk modeling
  • Hands-on experience with catastrophe modeling tools and exposure management frameworks
  • Proficiency in programming (Python/R) and data visualization tools
  • Familiarity with machine learning techniques and their application in insurance
  • Strong problem-solving skills and ability to communicate complex insights to non-technical stakeholders

What We're Looking For:
We value individuals who combine technical rigor with business intuition. You should be comfortable working in a dynamic environment, handling ambiguity, and driving innovation through data. A proactive mindset, attention to detail, and the ability to translate analytical findings into strategic recommendations will set you apart in this role.

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