Equifax

Senior Agentic AI Data Scientist – Model Risk Management

Equifax

full-time

Posted on:

Location Type: Hybrid

Location: Alpharetta • United States

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Job Level

Senior

Tech Stack

CloudOpen SourcePythonSQL

About the role

  • Design and execute specialized evaluation and monitoring strategies to assess GenAI workflows, focusing on multi-step reasoning, tool-use reliability, and "looping" risks where agents may fail in autonomous tasks
  • Critically evaluate and monitor GenAI-specific risks, including hallucinations, prompt injection vulnerability, and data leakage, ensuring that mitigation strategies (such as guardrails and RAG-based grounding) are robust and effective
  • Conduct research on emerging evaluators (e.g., "LLM-as-a-judge") and develop benchmarking standards to systematically assess GenAI application outputs, ensuring the system performs reliably on unstructured data where traditional statistical profiles do not apply
  • Develop and execute comprehensive stress-testing protocols to assess GenAI soundness and identify potential risks
  • Critically assess the completeness and accuracy of GenAI development documentation, code, and marketing materials
  • Develop and implement innovative validation approaches for complex and nontraditional models, including those with unstructured data and unique risk profiles
  • Develop AI Agent tools to automate the retrieval, wrangling, and analysis of data
  • Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to prepare datasets, conduct analytics, and develop deployable solutions with guidance from more senior resources
  • Develop and deploy AI and ML solutions on Google Cloud Platforms
  • Utilize massive data sources to craft business insights and features for innovative solutions
  • Understand diverse data sources, both structured and unstructured

Requirements

  • 5+ years of relevant experience in Data Science and/or AI/ML
  • M.S. or higher degree required in Computer Science; or Data Science, Analytics, Mathematics, Statistics, Economics, Operations Research, Industrial Engineering or a substantially related field of study if accompanied by strong computer science principles and skills
  • Solid experience with "classic" machine learning (XGBoost, Regression, Clustering) is highly desirable
  • Machine learning and deep learning fundamentals, natural language processing (NLP), cloud computing, multi-agent systems understanding, data analysis, programming proficiency, and a grasp of ethical considerations in AI development
  • Experience with agents frameworks (preferably Langchain)
  • Experience with proprietary and/or open source LLMs
  • Experience in prompt engineering
  • Experience with RAG and Vector Databases
  • Proficient in Python and SQL
Benefits
  • comprehensive compensation and healthcare packages
  • 401k matching
  • paid time off
  • organizational growth potential through our online learning platform with guided career tracks

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningdeep learningnatural language processingdata analysisXGBoostregressionclusteringprompt engineeringRAGvector databases
Soft skills
critical evaluationrisk assessmentinnovationproblem-solvingcommunication
Certifications
M.S. in Computer ScienceM.S. in Data ScienceM.S. in AnalyticsM.S. in MathematicsM.S. in StatisticsM.S. in EconomicsM.S. in Operations ResearchM.S. in Industrial Engineering