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AI Third-Party Model Risk Assessment Analyst

Noah Kovacs

Full-time · Job · Chicago

About the role

Our mission is to make AI explainable to non-technical stakeholders. This role extends that mission beyond models we build ourselves, into models our clients buy or license from outside vendors. We already have a strong internal toolkit for auditing bias, fairness, and explainability on models we train in-house. What we don't have yet is a repeatable process for assessing the risk of a third-party model our clients want to deploy, where we often only have documentation and a handful of test cases to go on. You'll build that assessment framework — a structured way to score vendor model risk from limited external evidence, and a Tableau reporting layer that lets client risk committees see the reasoning clearly.

Responsibilities

  • Design a risk assessment framework for evaluating third-party AI models
  • Score vendor models using available documentation and limited test access
  • Build Tableau reports summarizing risk findings for client risk committees
  • Collaborate with the internal fairness and explainability research team
  • Maintain a growing library of vendor model risk precedents

Requirements

  • Experience with model auditing, fairness, or explainability work
  • Statistics background for evaluating limited-evidence risk scenarios
  • SQL and scikit-learn experience
  • Tableau or equivalent reporting tool experience
  • Comfort working with incomplete external documentation

Benefits

  • Fully remote
  • Health insurance
  • Research publication support
  • Learning and development budget
  • Flexible PTO

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Categories

data science & analytics

Skills

python sql scikit-learn statistics tableau

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

data science & analytics

Skills

python sql scikit-learn statistics tableau

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