Model Governance Lead (Credit)

Plaid; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Office locations in SF, NYC, and RTP

Health benefits

Fertility support

Mental health support

Parental leave

Home office stipend

Daycare support

Commuting benefits

Job summary

Plaid is seeking a Model Governance Lead, Credit, to own and execute the governance program for its Credit products. You will work independently while partnering with model owners and cross-functional teams to challenge, identify risks, and improve governance practices over time.

You will build and evolve a model risk governance framework for Plaid’s Credit product portfolio, assess conceptual soundness, data, features, performance, stability, and intended use, and translate weaknesses into

Qualifications

• 7+ years of experience building and owning a model governance program.
• Strong understanding of machine learning concepts and defensible validation.
• Experience with model risk management, development, or data science in FinTech is a plus.
• Experience assessing data, features, performance, and intended use of credit models.

Responsibilities

• Own and execute the Model Governance program for Plaid’s Credit products.
• Partner with Product, Data Science, and Engineering to strengthen governance and validation practices.
• Identify risks, weaknesses, and remediation plans for credit models.
• Create clear, rigorous documentation to help customers understand models.

Skills

Model governance

Model validation

Model risk management

Data science

Machine learning

Credit models

XGBoost

Foundation models

Neural networks

FinTech experience

Tools

XGBoost

Job description

• As the Model Governance Lead, Credit, you will own and execute the Model Governance program for Plaid’s Credit products. You will help ensure that the models supporting Plaid’s Credit Score and Insights products are conceptually sound, appropriately validated, well-documented, and fit for their intended use
• You will work independently while partnering closely with model owners and cross-functional stakeholders. You will provide thoughtful challenge, identify risks and limitations, and help teams improve models and governance practices over time
• Building and evolving a model risk governance framework for an important Credit product portfolio
• Independently assessing the conceptual soundness, data, features, performance, stability, and intended use of credit models
• Identifying model weaknesses and translating them into clear, actionable remediation plans
• Partnering with Product, Data Science, and Engineering teams to strengthen model development and validation practices
• Creating clear, rigorous documentation that helps customers understand and trust the models behind Plaid’s Credit products
• Bringing curiosity, sound judgment, and constructive challenge to complex modeling decisions
• Helping shape responsible use of machine learning as Plaid develops new Credit scores and attributes

Benefits

• Vibrant offices in SF, NYC, and Raleigh-Durham—​with catered meals, happy hours, and clubs to keep you connected
• Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
• Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft

A genuinely independent, detail-oriented, and curious mindsetComfort providing meaningful challenge to model owners and stakeholders rather than simply documenting their workExperience in model validation, model risk management, model development, or Data Science7+ years of experience building and owning a model governance programStrong understanding of machine learning modeling concepts and techniques, such as XGBoost, and what constitutes rigorous, defensible model validationDeep knowledge of models built for credit purposesExperience assessing data and feature inputs, conceptual soundness, model performance, stability, limitations, and appropriateness of useExperience working at a FinTech is a plusFamiliarity with newer modeling techniques, such as foundation models and neural networks