Data Scientist, Model Risk Management

Data Scientist, Model Risk Management

Equifax is looking for a Data Scientist, Model Risk Management to join our world‑class Model Risk Management team. In this exciting role, you will have the opportunity to use cutting‑edge cloud technology to conduct model validation across a wide range of Risk, Fraud, and Generative AI applications, while ensuring high‑quality solutions and communicating critical results with partners across the organization.

• Hybrid work schedule: 2 days remote (Monday & Friday) and 3 days onsite (Tuesday, Wednesday, Thursday).
• Location:
  
  Alpharetta, Georgia or midtown Atlanta (OAC).
• Immigration sponsorship not offered.

• Conduct model validation to verify model quality and identify data anomalies using statistical and advanced machine learning approaches.
• Apply critical rigor and assess models built for various verticals including retail banking, auto lending, communications & utilities, mortgage, and payments. Experience in credit risk analytics preferred.
• Research new and advanced data science techniques as appropriate for specific solutions.
• Self‑motivate to learn quickly and conduct independent research on new modeling techniques; keep up to date with industry developments.
• Proficient in Python, SQL, and advanced computational languages/applications such as Big Query, Tensor Flow, Scala, SAS, and R.
• Communicate concisely in written and oral English; create model validation reports and present to senior management, supervisory authorities, and stakeholders.
• Team player, self‑motivated, disciplined, task‑focused; deliver high‑quality results within strict deadlines.

• 5–7 years of professional experience as a data scientist or statistical modeler in domains such as identity & fraud, credit risk, telecommunications, financial services, payments, ecommerce, B2B/B2C, marketing, insurance, or security analytics.
• Bachelor’s degree or higher in Data Science, Computer Science, Mathematics, Engineering, Operations Research, Statistics or related discipline. Master’s or PhD highly preferred.
• Strong quantitative analytical experience: statistics, regression modeling, neural networks, decision trees, random forest, support vector machine, kernel methods, clustering, and similar methods.
• Experience with advanced architecture including Deep Neural Networks, Generative AI, and Agentic AI frameworks highly desirable.

• Master’s Degree or PhD in a related discipline.
• Experience as a Data Scientist in the banking industry.
• Very strong written and verbal communication skills; influence stakeholders.
• Proven ability to quickly grasp complex concepts and identify potential model issues or validation gaps.
• Strong analytical skill, critical thinking and problem solving capabilities.
• Working knowledge of Google Cloud and other cloud environments.
• Experience in UNIX environment preferred.
• Ability to work independently with minimal guidance.

• Mid‑Senior level

• Full‑time

• Engineering and Information Technology