Risk & Actuarial AI Expert

Weekday AI

Job Overview

Location

Remote

Salary

USD 100 - 120 hourly

Employment Type

Part-time

Work Arrangement

Remote

Sector

Data & Analytics

Experience Level

Mid-level (3-5 years)

Application Deadline

May 6, 2026

About the Company

Weekday AI is at the forefront of revolutionizing hiring processes, backed by Y Combinator and recognized as a Product Hunt #1 product of the day. The company has established the largest database of white-collar talent in India and developed advanced outreach tools designed to achieve exceptional response rates.

Their mission is to build the next frontier in hiring, leveraging technology to connect employers with top-tier talent more effectively and efficiently. Weekday AI is committed to innovation in recruitment solutions.

Job Description

We are seeking a highly analytical and forward-thinking Risk & Actuarial AI Expert to join our growing team. This role sits at the intersection of actuarial science, risk management, and advanced analytics, leveraging artificial intelligence to enhance decision-making across insurance and risk portfolios.

The ideal candidate will bring a strong foundation in actuarial principles combined with hands-on experience in data science, enabling the transformation of complex risk data into actionable insights. You will play a central role in evaluating and optimizing portfolio performance through detailed loss ratio and combined ratio analysis, monitoring trends, and providing recommendations to improve underwriting profitability.

Furthermore, you will conduct comprehensive portfolio risk assessments using statistical models and AI-driven techniques, identifying risk concentrations and supporting strategic decisions. A significant part of the role will focus on catastrophe modeling and exposure management, enhancing traditional approaches with machine learning for improved prediction accuracy.

Leveraging modern AI/ML techniques to automate actuarial workflows, improve predictive modeling, and uncover hidden patterns in large datasets will be key. You will design and implement models that enhance pricing, reserving, and risk selection processes, with experience in Python, R, and cloud-based analytics platforms being valuable.

To apply for this role, click the Apply button on this page and follow the instructions.

Required Skills

Actuarial ScienceRisk ManagementData ScienceArtificial IntelligenceMachine LearningPythonRLoss Ratio AnalysisCombined Ratio AnalysisCatastrophe ModelingPortfolio Risk AssessmentData Visualization

Key Responsibilities

Evaluate and optimize portfolio performance through detailed loss ratio and combined ratio analysis.
Monitor trends, identify deviations, and provide recommendations to improve underwriting profitability.
Conduct comprehensive portfolio risk assessments using statistical models and AI-driven techniques.
Identify risk concentrations, assess diversification, and support strategic decisions related to risk selection and capital allocation.
Collaborate with underwriting, finance, and product teams to ensure alignment between risk appetite and business objectives.
Focus on catastrophe modeling and exposure management, assessing potential losses from natural disasters and extreme events.
Enhance traditional modeling approaches using machine learning techniques to improve prediction accuracy and scenario analysis.
Contribute to stress testing, scenario planning, and regulatory reporting requirements.
Leverage modern AI/ML techniques to automate actuarial workflows, improve predictive modeling, and uncover hidden patterns in large datasets.
Design and implement models that enhance pricing, reserving, and risk selection processes.

Qualifications

Bachelor’s or Master’s degree in Actuarial Science, Mathematics, Statistics, Data Science, or a related field.
Progress toward actuarial certification (e.g., IFoA, SOA, or equivalent) preferred.
2–8 years of experience in actuarial analysis, risk management, or insurance analytics.
Strong expertise in loss ratio and combined ratio analysis.
Proven experience in portfolio risk assessment and risk modeling.
Hands-on experience with catastrophe modeling tools and exposure management frameworks.
Proficiency in programming (Python/R) and data visualization tools.
Familiarity with machine learning techniques and their application in insurance.
Strong problem-solving skills and ability to communicate complex insights to non-technical stakeholders.

How to Apply

To apply for this role, click the Apply button on this page and follow the instructions.

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The insurance and risk management sector is rapidly integrating advanced AI to refine predictive modeling and enhance decision-making. This role is pivotal in leveraging artificial intelligence to optimize actuarial processes and risk assessments. Key technical keywords include loss ratio analysis, combined ratio analysis, catastrophe modeling, machine learning, and Python/R programming. The impact of this position is significant, directly influencing portfolio performance, underwriting profitability, and strategic risk allocation, thereby driving substantial business ROI and leadership scale in risk analytics.