Senior Agentic AI Data Scientist - Model Risk Management

Equifax • Alpharetta, GA

2d • Hybrid

About The Position

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. Equifax is looking for a Senior Agentic AI Data Scientist to join our world-class Data and Analytics Center of Excellence (D&A COE). In this exciting role, you will have the opportunity to use cutting edge cloud technology and develop various analytics related AI and ML solutions. Equifax has a hybrid work schedule that allows for 2 days of remote work (Monday and Friday), with 3 days onsite (Tuesday, Wednesday, Thursday) every week. This role reports to our office in Alpharetta, Georgia OR midtown ATL (OAC). This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support. This is a direct-hire role and is not open to C2C or vendors. What you will do 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.

Nice To Haves

• Exposure to Agentic AI.
• Exposure to Gen AI Governance.
• Evaluation, testing and monitoring of GenAI/Agents.
• Google Cloud Platform experience.

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.

Benefits

• comprehensive compensation and healthcare packages
• 401k matching
• paid time off
• organizational growth potential through our online learning platform with guided career tracks

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees