Apply on Employer Site

Equifax · 1 day ago

Senior Agentic AI Data Scientist - Model Risk Management

USA - Atlanta - One Atlantic Center

Full-time

Hybrid

Senior Level

5+ years exp

Equifax is where you can power your possible. In this role, you will have the opportunity to use cutting edge cloud technology and develop various analytics related AI and ML solutions.

AnalyticsConsultingDatabase

No H1B

Responsibilities

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

Qualification

Data ScienceAI/ML SolutionsPythonSQLGoogle Cloud PlatformMachine LearningNatural Language ProcessingData AnalysisPrompt EngineeringMulti-Agent SystemsEthical AI DevelopmentAgent FrameworksRAGVector Databases

Required

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