VP, Applied AI/ML for Compliance Risk

Next Frontier Capital; Jersey City (NJ); On-site; USD 190,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Data Scientist Vice President in its Compliance, Conduct Operational Risk Data Analytics organization. You will develop POCs and deployable AI/ML models, extract data from multiple sources, and transform it into analysis-ready formats for data pipelines.

You will work with data scientists, risk professionals, model validation, and technology partners to implement scalable analytics and document quantitative models for governance review.

Qualifications

• Six-plus years of Python/R/Scala in quantitative roles.
• Theoretical and applied ML/statistical modeling knowledge.
• Experience with graph ML and associated packages.
• Experience with LLM prompt engineering and fine tuning.
• Experience with cloud-based data pipelines and big data tooling.
• Familiarity with multiple databases and data integration.

Responsibilities

• Analyze complex/unstructured data to understand business problems and use cases.
• Design methodologies and quantify business use cases.
• Develop deployable models and analytics methods as part of a managed system.
• Collaborate with data scientists, risk professionals, and governance teams.
• Document quantitative models for internal model risk and governance review.

Skills

Python/R/Scala

ML/Statistics

LLM prompt engineering

Graph ML

Cloud data pipelines

Big data tooling

Education

Bachelor's degree in quantitative field

Tools

NetworkX

Torch-Geometric

GraphFrames

Graphistry

Pandas

Scikit-Learn

XGBoost

LightGBM

AutoML

Optuna

Hyperopt

Matplotlib

Seaborn

Geopandas

Job description

JPMorgan Chase & Co. is seeking a Data Scientist Vice President in its Compliance, Conduct Operational Risk Data Analytics organization. You will develop POCs and deployable AI/ML models, extract data from multiple sources, and transform it into analysis-ready formats for data pipelines.

You will work with data scientists, risk professionals, model validation, and technology partners to implement scalable analytics and document quantitative models for governance review.