Actuarial Data Scientist

Berkshire Hathaway GUARD Insurance Companies

Actuarial Data Scientist modernizing predictive pricing, risk segmentation, and profitability models for Berkshire Hathaway GUARD Insurance Companies. Building production-ready analytics for a nationwide property and casualty insurer.

Posted 8/20/2026full-timeNew York City • New York • 🇺🇸 United StatesMid-LevelSenior💰 $120,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing predictive models and advanced analytical solutions using Python and SQL, with a strong focus on actuarial methodologies and commercial lines products. Capable of communicating complex analytical findings to diverse audiences and driving the adoption of data-driven solutions across the organization.

Highest-signal resume keywords

Predictive ModelingPython ProgrammingAdvanced SQL SkillsActuarial MethodologiesCommercial Lines Products

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingStatistical Modeling TechniquesData AnalysisMachine Learning TechniquesAnalytical Solutions Development

Soft Skills

Strong CommunicationCollaborationProblem-SolvingStakeholder Management

Tools & Technologies

GitAzure DevOpsCI/CD ConceptsVersion Control

Industry Keywords

Actuarial ScienceData ScienceCommercial LinesRisk SegmentationUnderwriting Performance

Tech Stack

Tools & technologies

AzurePythonSQL

About the role

Key responsibilities & impact

Report to the AVP, Data Science & Commercial Lines Pricing
Partner with actuarial teams to develop analytical solutions improving pricing sophistication, risk segmentation, underwriting performance, and profitability
Develop and enhance pricing, segmentation, profitability, and risk selection models across Commercial Lines products using actuarial methodologies and 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
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
Communicate analytical findings and recommendations to technical and non-technical audiences, including senior leadership, and drive adoption of analytical solutions across the organization
Work in the NYC office 3 days per week and travel as required

Requirements

What you’ll need

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
Applicants must be authorized to work in the U.S. without current or future sponsorship
Experience working with actuarial pricing methodologies (preferred)
Experience with Commercial Lines products such as Workers Compensation, Commercial Auto, General Liability, Businessowners (BOP), Professional Liability, Umbrella, or similar coverages (preferred)
Experience leading actuarial or analytical modernization initiatives (preferred)
Familiarity with Git or Azure DevOps, code review processes, CI/CD concepts, package management, and collaborative development workflows (preferred)
Familiarity with model governance, validation, and monitoring frameworks (preferred)
Candidates with combined actuarial and data science backgrounds are strongly encouraged to apply

Benefits

Comp & perks

Hybrid schedule: 2 days remote / 3 days in-office
Competitive pay
Generous PTO
Medical, dental & vision starting day one
401(k)
Tuition reimbursement
Longevity bonuses
Short-term incentive plan (performance-based bonus), subject to individual and company performance