Equifax
Website:
theworknumber.com
Company:
https://www.linkedin.com/company/equifax
Seniority: Mid-Senior level
Industries: Financial Services
Job details:
The Data Scientist - Specialist at Equifax leads the Model Risk Management team in validating statistical and advanced AI models. This strategic role combines hands-on technical oversight, team mentorship, and advisory duties regarding risk governance and regulatory compliance. Candidates require 7+ years of quantitative experience, proven leadership skills, and expertise in emerging technologies like generative and agentic AI.
What You’ll Do
- Lead, manage, and mentor a high-performing team of model validators, ensuring their professional growth and development.
- Oversee the execution of multiple complex validation projects simultaneously, from test design to final delivery and communication.
- Foster a culture of critical thinking, continuous improvement, and effective risk management within the team.
- Collaborate with global partners to supervise validation projects, ensuring a consistent and technically sound approach to AI/Model Risk Management across non-direct reporting lines
- Perform and lead independent, hands-on model validations, including deep-dive analysis of model design, performance, and implementation.
- Develop and execute comprehensive validation test designs to assess model soundness and identify potential risks.
- Critically assess the completeness and accuracy of model documentation, code, and marketing materials.
- Conduct deep-dive research on emerging analytical techniques, with a particular focus on validating models using generative AI and agentic AI.
- Develop and implement innovative validation approaches for complex and nontraditional models, including those with unstructured data and unique risk profiles.
- Serve as a trusted advisor to model developers and business owners on model design, development, and risk mitigation strategies.
- Review and provide guidance on model monitoring plans and ongoing performance reports.
- Drive the enhancement of Model Risk Management procedures and standards to align with evolving regulatory requirements and industry best practices.
- Collaborate with key stakeholders across the organization, including marketing, technology, legal, compliance, and business owners, to ensure a robust model risk governance framework.
- Respond to and manage inquiries from clients, internal auditors, and regulators regarding model risk matters.
What Experience You Need
- Master’s degree in a quantitative field such as statistics, data science, computer science, mathematics, economics, or finance.
- 7+ years of industry experience in predictive modeling, data science, or a related quantitative field. Prior experience with credit risk model development and/or validation is highly preferred.
- A minimum of 3 years of experience managing a highly talented team with 6 or more direct reports is preferred.
- Strong knowledge of and hands-on experience with either advanced forecasting analytics (e.g., logistic regression, time series modeling, ML classification models)) or advanced machine learning techniques including generative AI and agentic AI.
- Extensive experience with Big Data environments and advanced computational processes.
- Demonstrated experience with model risk management and/or compliance is highly preferred.
- Exceptional critical thinking, problem-solving, and analytical skills.
- Proven ability to quickly grasp complex concepts and identify potential model issues or validation gaps.
- Excellent interpersonal, networking, verbal, and written communication skills, with a proven ability to write and edit high-quality technical reports.
- Proficiency with programming languages such as SAS, SQL, R, Python, Scala, and Spark.
- Hands-on experience with UNIX/LINUX and Google cloud environments.
- Highly detail-oriented, proactive, and efficient.
What Could Set You Apart
- Familiarity with regulatory requirements and guidelines related to Model Risk Management.
- Prior regulatory modeling development experience including ECL, Stress testing, CECL/IFRS9.
- First-hand experience on cloud-based platforms including GCP, Azure, or AWS.
- Exposure to AI agents, multi-agents and/or Agentic AI Frameworks.
- Excellent communication and presentation skills.
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