Insurance Underwriting AI Expert

Job not on LinkedIn

🕒 April 21

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Logo of Weekday (YC W21)

Weekday (YC W21)

11 - 50 employees

Founded 2021

☁️ SaaS

🎯 Recruiter

Human Resources • SaaS • Recruitment

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• 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.

🎯 Requirements

• 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.

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