Actuarial and Data Science Model Validation

The Hartford

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Hartford, CT
Salary
$108,000–$162,000 / yr
Posted
78 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $201k
This role $135k
$92k most similar roles pay here $256k

This role pays less than 88% of similar roles. Most pay $162,000–$240,312 — the shaded band above. At the midpoint, this role pays about $135k versus about $201k for comparable roles.

Based on 240 similar postings.

Employer

About The Hartford

The Hartford is a leading provider of property and casualty insurance, group benefits, and mutual funds, serving businesses and individuals across the United States. Industry: Insurance & Financial Services

The Hartford currently has 45 open roles on FindRole.

Listed pay typically runs $127,600–$191,400 across 37 roles with salary data.

Most-posted roles

View all roles at The Hartford

At a glance

TL;DR · Actuarial and Data Science Model Validation

Actuarial and Data Science Model Validation. The Risk Manager joins the Model Risk Management team to ensure the integrity, accuracy, and compliance of AI and Generative AI models across various business functions. This role involves independently reviewing, challenging, and validating models against internal standards, regulatory expectations, and ethical principles. Day-to-day responsibilities include designing challenger solutions for tasks like summarization and data synthesis, assessing prompt engineering, and evaluating model outputs for accuracy. The candidate will also improve validation frameworks, track remediation findings, and educate the enterprise on modeling best practices. Required skills include proficiency in Python, R, SAS/SQL, and experience with tools such as Vertex AI, LangChain, HuggingFace, and OpenAI APIs. The role addresses risks associated with advanced analytics, machine learning algorithms, and traditional actuarial models within a complex insurance environment.

What you'll do

  • Validate AI and GenAI models across various business lines to ensure accuracy, reliability, and compliance with internal standards.
  • Design and build challenger solutions and testing methods for tasks like summarization, question answering, and data synthesis.
  • Assess key model components including data inputs, assumptions, prompt engineering, and context engineering.
  • Evaluate quantitative and qualitative testing techniques to ensure the robustness of machine learning algorithms.
  • Identify risks and provide recommendations to mitigate issues through detailed model validation reports.
  • Manage governance tasks including tracking findings, remediation testing, and reporting results to internal stakeholders.
  • Enhance GenAI validation frameworks by implementing standardized metrics and advanced validation tools.
  • Monitor emerging AI technologies and regulatory changes to update internal risk management policies and guidelines.

What we're looking for

  • Hold an advanced degree (M.S. or Ph.D.) in a relevant field such as AI, Machine Learning, Statistics, or Computer Science.
  • Possess 3+ years of industry experience in machine learning or data science.
  • Possess at least 1 year of experience specifically focused on Generative AI.
  • Demonstrate strong programming skills across platforms including Python, R, and SAS/SQL.
  • Maintain a solid understanding of GenAI concepts including prompt engineering, RAG, agent workflows, and neural networks.
  • Experience with tools such as Vertex AI, LangChain, HuggingFace, or OpenAI APIs is required.
  • Possess strong analytical, critical thinking, and the ability to communicate complex technical concepts to non-technical stakeholders.
  • Ability to work independently with proactive self-directed accountability and a commitment to continuous learning in AI technologies.

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