Vice President, Credit Risk Data Science & ML Strategy

JPMorganChase; Wilmington (DE); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health care coverage

Retirement plan

Tuition reimbursement

Job summary

JPMorgan Chase in Risk Management and Compliance seeks a Vice President — Credit Risk Data Science to lead feature engineering and ML initiatives powering credit risk decisions across Chase sub-lines. You will design scalable risk attribute libraries and production-grade models while collaborating with risk, technology, data governance, and controls partners to ensure robust documentation and lineage.

Your leadership will extend to transformer-based models and LLM-enabled analytics, driving

Qualifications

• 5+ years building predictive models and data attributes.
• Production-grade coding experience in data science stacks.
• Experience with ML frameworks and cloud platforms.

Responsibilities

• Lead design, governance of an enterprise Risk Attribute Library.
• Ensure feature reuse and quality across customer lifecycles.
• Prototype and productionize advanced feature engineering methods.
• Engineer features from large-scale structured data.
• Build scalable ML and deep learning models, including transformers.
• Apply LLM techniques to extract signals from unstructured text.
• Establish data quality tests and monitoring for drift and leakage.
• Collaborate with risk, governance, technology, and controls partners.
• Communicate complex analytics clearly to technical and non-technical stakeholders.

Skills

Feature engineering

Model design

Data governance

Cross-functional

Education

Master0s degree in Computer Science/Statistics/Engineering

PhD preferred

Tools

Python

SAS

Apache Spark

Scala

TensorFlow

AWS

Snowflake

Databricks

Job description

JPMorgan Chase in Risk Management and Compliance seeks a Vice President — Credit Risk Data Science to lead feature engineering and ML initiatives powering credit risk decisions across Chase sub-lines. You will design scalable risk attribute libraries and production-grade models while collaborating with risk, technology, data governance, and controls partners to ensure robust documentation and lineage.

Your leadership will extend to transformer-based models and LLM-enabled analytics, driving