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Actuarial Machine Learning Jobs (NOW HIRING)

Pricing Actuary

New York, NY · On-site

$170K - $220K/yr

Our SaaS platform uses transparent machine learning and predictive analytics to improve the speed, accuracy, and reliability of actuarial pricing and reserving. Built by experienced actuarial ...

Pricing Actuary

Boston, MA · Remote

$170K - $220K/yr

Our SaaS platform uses transparent machine learning and predictive analytics to improve the speed, accuracy, and reliability of actuarial pricing and reserving. Built by experienced actuarial ...

Pricing Actuary

New York, NY · Remote

$170K - $220K/yr

Our SaaS platform uses transparent machine learning and predictive analytics to improve the speed, accuracy, and reliability of actuarial pricing and reserving. Built by experienced actuarial ...

Pricing Actuary

Chicago, IL · Remote

$170K - $220K/yr

Our SaaS platform uses transparent machine learning and predictive analytics to improve the speed, accuracy, and reliability of actuarial pricing and reserving. Built by experienced actuarial ...

Pricing Actuary

Atlanta, GA · Remote

$170K - $220K/yr

Our SaaS platform uses transparent machine learning and predictive analytics to improve the speed, accuracy, and reliability of actuarial pricing and reserving. Built by experienced actuarial ...

In this role, you will partner with analysts & data scientists to scope & execute actuarial analyses rooted in machine learning. The ideal candidate would have at least 5 years of actuarial ...

In this role, you will partner with analysts & data scientists to scope & execute actuarial analyses rooted in machine learning. The ideal candidate would have at least 5 years of actuarial ...

It allows for efficient training of large scale machine learning models, but it also has to serve ... You'll work closely with Sean Chin, our Head Actuary, to translate business and modelling ...

It allows for efficient training of large scale machine learning models, but it also has to serve ... You'll work closely with Sean Chin, our Head Actuary, to translate business and modelling ...

... machine learning techniques. The Lead Actuarial Predictive Modeler works directly with loss cost models, including developing new rating features as well as acquisition, retention and conversion ...

... machine learning techniques. The Lead Actuarial Predictive Modeler works directly with loss cost models, including developing new rating features as well as acquisition, retention and conversion ...

Showing results 41-60

Actuarial Machine Learning information

See salary details

$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.

Actuarial Data Scientist

Pelham, NY • On-site

$120K - $190K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


Job description

Overview

Good Things Start Here.

Good things are happening at Berkshire Hathaway GUARD Insurance Companies—an A+ (Superior) rated, nationwide Property & Casualty insurer backed by Berkshire Hathaway. With supportive leadership, collaborative teams, and opportunities to grow, GUARD is a place where people build meaningful, long‑term careers.

Good Things You Can Count On.

  • Hybrid schedule: 2 days remote / 3 in‑office
  • Competitive pay + generous PTO
  • Medical, dental & vision starting day one
  • 401(k), tuition reimbursement & longevity bonuses
Responsibilities

We're seeking an Actuarial Data Scientist that would be reporting to the AVP, Data Science & Commercial Lines Pricing. Thisrole combines actuarial analytics, predictive modeling, and technical leadership to advance pricing sophistication, risk segmentation, underwriting performance, and profitability. The successful candidate will help modernize actuarial modeling practices, develop scalable analytical solutions, and promote the adoption of data science and software engineering best practices throughout the organization.

Day-to-day:

  • Partner with actuarial to develop analytical solutions that improve pricing sophistication, risk segmentation, underwriting performance, and profitability.
  • Develop and enhance pricing, segmentation, profitability, and risk selection models across Commercial Lines products using both actuarial methodologies and modern machine learning techniques.
  • Apply advanced analytics to pricing, underwriting, claims, and other insurance datasets to identify trends, emerging risks, and opportunities for profitable growth.
  • Support rate reviews, indication analyses, profitability studies, portfolio management, and other pricing initiatives through advanced analytical techniques.
  • Develop predictive models using GLMs and other statistical and machine learning approaches while balancing predictive performance, business value, interpretability, and regulatory considerations.
  • Research and evaluate internal and external data sources to enhance underwriting, pricing, and portfolio insights.
  • Build scalable, production-ready analytical workflows and collaborate with data engineering and technology teams to operationalize models and analytical solutions.
  • Promote best practices in model development, coding standards, testing, documentation, version control, reproducibility, model governance, and performance monitoring.
  • Provide technical guidance and mentorship to actuarial and analytical teams, helping advance the adoption of modern data science and software development practices.
  • Communicate analytical findings and recommendations to technical and non-technical audiences, including senior leadership, and help drive adoption of analytical solutions across the organization.
Qualifications

Required

  • Bachelor's degree in Actuarial Science, Statistics, Mathematics, Data Science, Computer Science, Engineering, Economics, or a related quantitative field.
  • 3-5 years of experience in Actuarial Data Science field
  • Experience developing predictive models and advanced analytical solutions in a business environment.
  • Strong proficiency in Python, including development of production-quality analytical code.
  • Advanced SQL skills for large-scale data extraction, transformation, and analysis.
  • Experience working with large, complex datasets and statistical modeling techniques.
  • Strong communication, collaboration, problem-solving, and stakeholder management skills.
  • Ability to work independently in a fast-paced environment.

Preferred

  • Experience working with actuarial pricing methodologies.
  • Experience with Commercial Lines products such as Workers Compensation, Commercial Auto, General Liability, Businessowners (BOP), Professional Liability, Umbrella, or similar coverages.
  • Experience leading actuarial or analytical modernization initiatives.
  • Familiarity with Git or Azure DevOps, code review processes, CI/CD concepts, package management, and collaborative development workflows.
  • Familiarity with model governance, validation, and monitoring frameworks.
  • Candidates with combined actuarial and data science backgrounds are strongly encouraged to apply.

Applicants must be authorized to work in the U.S. without current or future sponsorship

Salary Range:

$120,000 – $190,000.

In addition to base salary, this role will be eligible for a short-term incentive plan (performance-based bonus), subject to individual and company performance.

The annual base salary range posted represents a broad range of salaries around the U.S. and is subject to many factors including but not limited to credentials, education, experience, geographic location, job responsibilities, performance, skills and/or training.

The successful candidate is expected to work in our NYC office 3 days per week and also be available for travel as required.

Interview Integrity Notice: Berkshire Hathaway GUARD is committed to a fair and consistent hiring process. Candidates are expected to participate independently in interviews. Unauthorized recording, transcription, AI note-taking, or AI interview assistance tools may not be used during interviews without prior approval.

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