Actuarial Data Scientist

Jobtailor; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Jobtailor in New York is seeking a data science professional specialized in actuarial pricing to join our growing analytics team. You will report to the AVP and collaborate with actuarial and product teams to build predictive models and data pipelines for pricing and profitability.

The role emphasizes production-grade code in Python and SQL, model governance, and the ability to communicate complex results to senior leadership. Hybrid NYC office 3 days/week, with travel as needed.

Qualifications

• Bachelor's degree in a quantitative field as listed.
• 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 production‑quality analytics code.
• Advanced SQL skills for large-scale data extraction, transformation, and analysis.
• Experience with actuarial pricing methodologies (preferred).
• Experience with Commercial Lines products such as Workers Compensation, Commercial Auto, General Liability, BOP, Professional Liability, Umbrella, or similar coverages (preferred).

Responsibilities

• Partner with actuarial teams to improve pricing sophistication, risk segmentation, underwriting performance, and profitability.
• Develop pricing, segmentation, profitability, and risk‑selection models for Commercial Lines using actuarial methods and ML.
• Apply analytics to pricing, underwriting, and claims data to spot trends and opportunities for profitable growth.
• Build production‑ready workflows and work with data engineering to operationalize models.
• Ensure governance, testing, documentation, and version control for reproducible analytics.
• Communicate findings to senior leadership and drive adoption of analytics across the org.

Skills

Python

SQL

Actuarial methodologies

Machine learning

Communication

Stakeholder management

Education

Bachelor's degree in Actuarial Science, Statistics, Mathematics, Data Science, Computer Science, Engineering, Economics, or related quantitative field

Tools

Git

Azure DevOps

CI/CD concepts

Version Control

Job description

• 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

• 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

Core Competencies

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 Modeling
• Python Programming
• Advanced SQL Skills
• Actuarial Methodologies
• Commercial Lines Products

ATS Optimization Keywords

Hard Skills

• Predictive Modeling
• Statistical Modeling Techniques
• Data Analysis
• Machine Learning Techniques
• Analytical Solutions Development

Soft Skills

• Strong Communication
• Collaboration
• Problem-Solving
• Stakeholder Management

Industry Keywords

• Actuarial Science
• Data Science
• Commercial Lines
• Risk Segmentation
• Underwriting Performance

Tools & Technologies

• Git
• Azure DevOps
• CI/CD Concepts
• Version Control