Compliance - Applied AI/ML Lead - Vice President

Testing Site - JPMC; New York (NY); On-site; USD 180,000 - 300,000; Full time

Job summary

JPMorgan Chase seeks a Data Scientist VP in Risk Management and Compliance to design and deploy AI/ML models, build scalable data pipelines, and translate complex data into actionable insights for governance and risk management. You will work with cross-functional teams to deliver deployable analytics and POCs across large data sets.

The role requires leadership in model development, strong communication, and experience with graph analytics and cloud-based data platforms.

Qualifications

• 6+ years of related experience in Python, R or Scala with Bachelor of Science degree in Computer Science, Physical Sciences, Econometrics, Statistics, or other quantitative discipline.
• Demonstrable theoretical and application knowledge of Machine Learning methods, and/or Statistical Models.
• Hands-on experience with graph analytics, graph-based learning, and graph representation/visualization.
• Experience with cloud platforms and data pipelines.

Responsibilities

• Analyze complex/unstructured data to understand the business problem and use case.
• Analyze business requirements, design, and develop appropriate methodology.
• Develop deployable, scalable and effective models/analytical methods as part of technology managed system or self-served application.
• Collaborate with data scientists, risk professionals, model validation teams, and technology partners.
• Prepare technical documentation of quantitative models for internal model risk and governance review.

Skills

Python/ R/ Scala

ML/ Statistical models

Data extraction/ pipelines

Communication

Education

Bachelor's degree in Computer Science or quantitative field

Tools

NetworkX

Torch-Geometric

Graphframes

Graphistry

Pandas

Scikit-Learn

XGBoost

LightGBM

CatBoost

Optuna

Hyperopt

Matplotlib

Seaborn

Geopandas

Hive

Cypher

TigerGraph

Neo4j

AWS

GCP

Azure

Databricks

Job description

Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

As a Data Scientist Vice President within the Compliance, Conduct Operational Risk Data Analytics organization, you will be responsible for devising and developing Proofs of Concept (POCs) and deployable models using AI/ML techniques, algorithms and other statistical and numerical methods. You will need to able to extract and work with large volumes of data (both structured and unstructured) from multiple sources, transforming it into an analysis-ready format to develop the data pipeline. Additionally, you are expected to independently formulate methodologies, and quantitative and analytical tasks, from business problems.

Job Responsibilities

• Analyze complex/unstructured data to understand the business problem and use case
• Analyze business requirements, design, and develop appropriate methodology
• Develop deployable, scalable and effective models/ analytical methods as part of technology managed system or as a self-served application of a business user
• Work collaboratively and creatively with other data scientists, technology partners, risk professionals, model validation teams, etc.
• Prepare technical documentation of quantitative models for internal model risk and governance review

Required qualifications, capabilities, and skills

• 6+ years of related experience in Python, R or Scala with Bachelor of Science degree in Computer Science, Physical Sciences, Econometrics, Statistics, or other any quantitative discipline.
• Demonstrable theoretical and application knowledge of Machine Learning methods, and/or Statistical Models
• Demonstrable hands‑on experience and familiarity with any or all of the following packages, algorithms, and/or alternatives, including Graph Learning Packages : (NetworkX, Torch‑Geometric, Graphframes, Graphistry),ML Packages (Pandas, Scikit‑Learn, XGBoost, catboost, lightgbm, automl, Optuna, Hyperopt), Visualization Packages (Matplotlib, Seaborn, Geopandas), Algorithm (Ensemble Louvian / Hierarchical Clustering, Label Propagation, Connected Component Analysis, Graph Neural net (Graph Attention Network), Page Rank, Centrality Analysis, Tree based Analysis, Outlier Detection Methods, Zero Shot/ Few Shot learning)
• Demonstrable experience with graph analytics, graph‑based learning, and graph representation/visualization
• Experience in graph Database: TigerGraph, Neo4j
• Experience in Query Language: Hive, Cypher (Graph Query Language)
• Hands‑on professional experience in software development especially with analytical & computationally intensive systems, digital transformations leveraging cloud technologies (AWS, GCP, Azure, Databricks etc.)
• Experience in developing and operationalization of data pipelines
• Familiarity and experience of assimilating large amounts of data from multiple databases and utilize them for creating actionable outcome; Adhering to a standardized analysis and project methodology; and Documenting quantitative analysis

Preferred qualifications, capabilities, and skills

• Post graduate degrees such as Master’s Degree, PhD, etc. is preferred
• Working knowledge of C/C#/C++ or others is a plus
• Real life exposure to Agile SDLC, ModelOps and /Or Design Thinking is desirable.
• Familiarity with Natural Language Processing techniques is a plus
• Self‑starter and strong influencing skills with strong communication skills
• Experience in financial services industry and/ or, experience with process, controls and governance of a highly regulated environment