Compliance - Applied AI/ML Lead - Vice President

JPMorgan Chase & Co.
New York, United States of America
13 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 205K

Job location

New York, United States of America

Tech stack

Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Artificial Neural Networks
Azure
Big Data
C Sharp (Programming Language)
C++
Cloud Computing
Cluster Analysis
Databases
Query Languages
Graph Database
Hive
Python
Machine Learning
Natural Language Processing
Neo4j
Software Engineering
Unstructured Data
Component Analysis
Google Cloud Platform
Model Validation
Pandas
Matplotlib
Scikit Learn
Information Technology
Data Analytics
XGBoost
Data Pipelines
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

Requirements

  • 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

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process., New York,NY $133,000.00 - $205,000.00 / year; Jersey City,NJ $133,000.00 - $205,000.00 / year

About the company

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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