Senior Data Scientist – AI

Arrowhead Programs

Senior Data Scientist role at Arrowhead Intermediaries focusing on AI-driven underwriting. Prototyping data pipelines and enhancing risk selection and pricing models in collaboration with actuaries.

Posted 5/1/2026full-timeSan Diego • California • 🇺🇸 United StatesSenior💰 $120,000 - $160,000 per yearWebsite

Tech Stack

Tools & technologies

AzureCloudPython

About the role

Key responsibilities & impact

Identify, extract, and integrate non-traditional data sources into underwriting and pricing workflows using generative AI, LLMs, and AI-assisted pipeline development.
Prototype, build, and iterate on data enrichment pipelines rapidly, validating signal quality and relevance before integration into production models – expanding the team’s data capabilities without traditional engineering dependencies.
Design, build, and maintain advanced predictive models for risk frequency, severity, and loss ratio that directly inform point-of-sale underwriting decisions.
Collaborate closely with actuaries and fellow data scientists to ensure all models are actuarially sound, statistically defensible, and aligned with pricing objectives.
Own models end-to-end — from hypothesis formation and data collection through to production deployment and ongoing monitoring.
Apply the latest generative AI tools, agentic frameworks, and LLM capabilities to real underwriting and pricing problems — staying current on developments and evaluating new approaches proactively.
Ensure all solutions are maintainable, well-documented, and consistent with established team standards for reproducibility and deployment.
Partner directly with underwriters and business leaders to understand portfolio needs, translate business problems into analytical solutions, and communicate findings clearly to non-technical stakeholders.
Serve as a technical authority and mentor for the broader data science team — elevating the team's fluency in generative AI tooling and best practices.
Contribute to a collaborative, standards-driven team environment where your work can be maintained and built upon by others.

Requirements

What you’ll need

5+ years of experience in data science or applied machine learning, with demonstrated end-to-end model ownership from data collection through production deployment.
Hands-on experience with large language models and generative AI frameworks, including Microsoft Foundry and/or Azure OpenAI endpoints, as well as LLM orchestration tools such as LangChain, LangGraph, or equivalent R-based tools such as ellmer.
Proficiency in R and/or Python, with comfort working across both languages in a production environment.
Strong foundation in statistical modeling, including GLMs, gradient boosting, and other techniques used for risk assessment and pricing.
Experience building and deploying models in cloud-based production environments (Azure preferred).
Demonstrated ability to communicate complex technical findings clearly to business stakeholders (written, verbal, and data visualization).
A strong appreciation for contributing and maintaining well-written documentation.
You value version control (git).
Strong problem-solving orientation with a bias toward action and delivery.

Benefits

Comp & perks

Health Benefits : Medical/Rx, Dental, Vision, Life Insurance, Disability Insurance
Financial Benefits : ESPP; 401k; Student Loan Assistance; Tuition Reimbursement
Mental Health & Wellness : Free Mental Health & Enhanced Advocacy Services
Beyond Benefits : Paid Time Off, Holidays, Preferred Partner Discounts and more.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data scienceapplied machine learningend-to-end model ownershiplarge language modelsgenerative AI frameworksstatistical modelingGLMsgradient boostingcloud-based production environmentsdata visualization

Soft Skills

communicationproblem-solvingcollaborationmentorshipdocumentationtranslating business problemsteam standards adherenceaction orientationdelivery focusstakeholder engagement