Senior Data Scientist

Trusted Resource Underwriters; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

TRUE Property Insurance is seeking a Senior Data Scientist to turn data into strategic business insights and help scale analytics capabilities across the organization.

You will lead predictive and prescriptive analytics efforts, translate models into practical business solutions, and collaborate with Product, Actuarial, Underwriting, and Technology teams to deploy models in production. Insurance experience is highly valued.

Qualifications

• 5+ years in data science, predictive modeling, or analytics, incl. 2+ years at Senior level.
• P&C insurance experience strongly preferred; homeowners insurance experience is a plus.
• Master's degree or higher in statistics, ML, CS, or a quantitative discipline.
• Strong understanding of statistical modeling and machine learning methods with business application.
• Experience developing and applying GLMs.
• Advanced programming skills in Python and SQL; R valued.
• Experience with large, complex datasets and data preparation for modeling.
• Solid understanding of DS and software development best practices, including version control and reproducibility.
• Experience with cloud-based DS environments; AWS and SageMaker preferred.
• Exposure to deep learning methodologies is a plus.

Responsibilities

• Lead end-to-end predictive modeling initiatives for pricing, underwriting, conversion, and retention.
• Apply statistical, machine learning, and deep learning techniques to develop models.
• Translate analytical insights and model outputs into actionable business solutions for stakeholders.
• Collaborate with Technology to deploy models in production environments.
• Extract, clean, transform, and analyze data from diverse sources.
• Apply modeling practices across feature engineering, imputation, model selection, validation, and tuning.
• Develop well-organized, production-ready analytical code.
• Communicate modeling approaches, results, limitations, and business value to technical and non-technical audiences.
• Advance data science capabilities and best practices as the organization scales.

Skills

Python

SQL

Statistical modeling

Machine learning

Deep learning

GLMs

Data analysis

Communication

Education

Master's degree or higher in a quantitative field

Tools

SageMaker

AWS

Git

Python

SQL

R

Job description

TRUE Property Insurance is a reciprocal insurer founded in 2020 to serve homeowners in storm-prone regions across Florida and other coastal markets throughout the United States. Today, TRUE writes HO3 business in Florida, Georgia, Texas, and South Carolina and continues to expand its geographic footprint. Through a partnership-driven distribution model, we collaborate with both new and established partners to deliver tailored homeowners insurance solutions while expanding our products, underwriting capabilities, technology, and team.

Job Description

Our growing Data Science and Analytics team is looking for a Senior Data Scientist with a curious, analytical mindset and a passion for solving complex business problems with data. This is an opportunity to join a fast-moving, entrepreneurial environment where you can help build new capabilities, influence business decisions, and grow your career as the company scales.

The ideal candidate brings strong experience in predictive and prescriptive analytics, excellent programming skills, and the ability to translate sophisticated models into practical business solutions. Experience within P&C insurance, particularly homeowners insurance, is highly valued.

Reporting to the Data Science and Analytics leader, this role will partner closely with Product, Actuarial, Underwriting, and Technology teams.

Primary Responsibilities

• Lead end-to-end predictive modeling initiatives supporting areas such as pricing and rating, underwriting and eligibility, conversion, retention, and other business applications.
• Apply statistical, machine learning, and deep learning techniques to develop supervised, semi-supervised, and unsupervised models based on business needs.
• Partner with Product, Actuarial, Underwriting, and other business teams to translate analytical insights and model outputs into actionable business solutions.
• Collaborate with Technology teams to operationalize and implement models in production environments.
• Extract, clean, transform, and analyze data from a variety of structured and unstructured sources.
• Apply strong modeling practices across feature engineering, data transformation, imputation, model selection, validation, evaluation, and tuning.
• Develop well-organized, maintainable, and production-ready analytical code.
• Clearly communicate modeling approaches, results, limitations, and business value to both technical and non-technical stakeholders.
• Help advance TRUE's data science capabilities, tools, methodologies, and best practices as the organization continues to scale.

Qualifications

• 5+ years of professional data science, predictive modeling, or advanced analytics experience, including at least 2 years operating at a Senior Data Scientist level.
• P&C insurance experience strongly preferred; homeowners insurance experience is a plus.
• Master's degree or higher in Statistics, Machine Learning, Computer Science, Applied Mathematics, Economics, Physics, or another quantitative discipline.
• Strong understanding of statistical modeling and machine learning methodologies, with demonstrated experience applying them to real-world business problems.
• Experience developing and applying Generalized Linear Models (GLMs) is important for this role.
• Advanced programming skills in Python and SQL; experience with R is highly valued.
• Strong experience working with large, complex datasets and extracting, cleaning, transforming, and preparing data for modeling.
• Solid understanding of software development and data science best practices, including code organization, reproducibility, version control, model validation, and production readiness.
• Experience with version control systems, preferably Git.
• Experience with cloud-based data science and machine learning environments; AWS and SageMaker experience preferred.
• Exposure to deep learning methodologies and applications is a plus.

Additional Valuable Experience

• Experimental design and causal inference.
• Experience with NoSQL or graph databases.
• Experience developing performant APIs and consuming APIs at scale.
• Experience deploying, monitoring, and maintaining machine learning models in production.
• Familiarity with modern AI-assisted development tools, including Claude Code.

We're Looking For

Beyond technical expertise, we're looking for someone who enjoys building. You should be comfortable working in an environment where priorities can evolve quickly, solutions are not always predefined, and data science is expected to have a direct impact on business decisions. The right candidate will combine technical depth with intellectual curiosity, strong business judgment, and the ability to collaborate effectively across disciplines.