Senior Agentic AI Data Scientist - Model Risk Management

Qualifications

• 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
• 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
• Evaluation, testing and monitoring of GenAI/Agents
• Google Cloud Platform experience

Benefits

• Exposure to Agentic AI
• Exposure to Gen AI Governance

Responsibilities

• 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 is a direct-hire role and is not open to C2C or vendors
• 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

Full Description

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.

What experience you need

• 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.

What could set you apart

• Exposure to Agentic AI.

• Exposure to Gen AI Governance.

• Evaluation, testing and monitoring of GenAI/Agents.

• Google Cloud Platform experience.

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