Insurance Underwriting AI Expert

Weekday AI (YC W21); France; Sur place; EUR 137 760 - 165 312; Temps partiel

Résumé du poste

Weekday AI (YC W21) is looking for an Insurance Underwriting AI Expert to transform traditional underwriting using AI techniques. The role involves designing and implementing AI/ML models to optimize risk assessment and develop robust pricing strategies. With a focus on collaboration across various teams, you will ensure compliance with regulatory standards while enhancing decision-making processes. Candidates should have a strong educational background and hands-on experience in underwriting and analytics. This position offers flexibility with remote work options.

Qualifications

• 2-8 years of experience in insurance underwriting or analytics, preferably with AI/ML.
• Strong understanding of underwriting principles and pricing strategies.
• Experience with data preprocessing and feature engineering.

Responsabilités

• Design and implement AI/ML models for risk assessment and selection.
• Translate guidelines into data models to automate decision-making.
• Develop policy pricing models using machine learning techniques.

Connaissances

Insurance underwriting

Machine learning

Data analysis

Statistical modeling

Risk assessment

Python

SQL

R

Formation

Bachelor's or Master's degree in Insurance, Actuarial Science, Data Science, or Statistics

Outils

Data visualization tools

Machine learning frameworks

Description du poste

Compensation

$100-$120 per hour (20 hours per week commitment)

Job Type

Part-time / Contract

Location

US, UK, Canada, France, Portugal (remote)

Overview

We are seeking a highly motivated Insurance Underwriting AI Expert to join our growing team. This role sits at the intersection of insurance domain expertise and advanced analytics, focusing on transforming traditional underwriting processes using AI-driven solutions. The ideal candidate will bring strong knowledge of underwriting fundamentals along with the ability to design, implement, and optimize intelligent systems that enhance decision‑making, efficiency, and risk outcomes.

As an Underwriting AI Expert, you will play a critical role in modernizing underwriting workflows by embedding data‑driven insights into core processes such as risk assessment, pricing, and portfolio management. You will collaborate closely with underwriting, actuarial, product, and engineering teams to develop scalable AI solutions aligned with business objectives.

Key Responsibilities

• Design and implement AI/ML models to support risk assessment and selection, improving accuracy in evaluating applicant profiles, exposures, and potential losses.
• Translate underwriting guidelines and business rules into data models and algorithms that automate and augment decision‑making.
• Develop and refine policy pricing and rating models using statistical and machine learning techniques, ensuring alignment with market competitiveness and profitability goals.
• Analyze historical data and external datasets to identify risk patterns, trends, and anomalies that inform underwriting strategies.
• Support appetite evaluation and guideline application by building intelligent systems that dynamically match risks to underwriting appetite and highlight exceptions.
• Collaborate with cross‑functional stakeholders to integrate AI models into underwriting platforms and workflows.
• Continuously monitor model performance, validate outputs, and recalibrate algorithms to ensure compliance, fairness, and accuracy.
• Contribute to the development of underwriting dashboards, reporting tools, and decision‑support systems.
• Stay updated on regulatory requirements and ensure all AI‑driven underwriting practices adhere to compliance standards.

Required Skills & Qualifications

• Bachelor's or Master's degree in Insurance, Actuarial Science, Data Science, Statistics, or a related field.
• 2-8 years of experience in insurance underwriting, analytics, or AI/ML applications within the insurance domain.
• Strong understanding of underwriting principles, including risk evaluation, pricing strategies, and policy structures.
• Hands‑on experience with machine learning techniques such as regression, classification, clustering, and predictive modeling.
• Proficiency in tools such as Python, R, SQL, and data visualization platforms.
• Experience working with large datasets, data preprocessing, and feature engineering.
• Familiarity with underwriting systems, rating engines, and insurance data structures is highly preferred.
• Strong analytical thinking, problem‑solving abilities, and attention to detail.

Preferred Qualifications

• Exposure to commercial or personal lines underwriting.
• Experience with AI model deployment and MLOps practices.
• Knowledge of regulatory frameworks impacting underwriting and pricing.