Come join our dynamic Know Your Customer (KYC) Quality Assurance (QA) Data and Analytics Team to support and implement our efforts in ensuring compliance, data reporting.

As an Analytics Solutions Associate at JP Morgan Chase, you will design, implement, and maintain programmatic frameworks to support KYC QA testing and quality reviews, including building Python-based automation tools and applying statistical techniques to support QA conclusions. You will integrate data from internal systems and APIs, partner with QA leads and risk managers to identify control gaps, and drive continuous improvement of QA processes through automation and standardization. Additionally, you will perform data quality checks, produce clear documentation for audit and regulatory review, and support governance processes by interfacing with compliance and legal teams.

Job Responsibilities: 

Design, implement, and maintain programmatic frameworks to support KYC QA testing and quality reviews  Build Python-based automation tools to generate samples, validate inputs, track coverage, and document methodology  Apply statistical techniques (e.g., confidence intervals, error rates, stratified sampling) to support QA conclusions  Integrate data from internal systems and APIs to support sampling, testing, and workflow automation  Partner with QA leads, risk managers, and operations teams to identify control gaps and translate testing requirements into analytical solutions Drive continuous improvement of QA processes through automation and standardization Perform data quality checks and exception analysis to ensure outputs are accurate and defensible  Produce clear documentation of sampling logic, assumptions, and methodologies for audit and regulatory review  Support governance processes by interfacing with AI risk, compliance, and legal teams, and managing required documentation and forms 

Required Qualifications, Capabilities and Skills:  

Bachelor’s degree in Computer Science, Economics, Statistics, Mathematics, or a related quantitative field  Experience in analytics, QA analytics, risk, controls, or operations analytics  Adaptability and willingness to shift focus as business priorities and automation needs change Intermediate Python programming skills, including scripting and data manipulation Intermediate knowledge of statistics, particularly sampling methodologies and error measurement Experience working with APIs or structured data feeds Familiarity with IDE-based development environments (e.g., VS Code, PyCharm) Basic UNIX/Linux command line skills Strong attention to detail and comfort working in controlled, highly regulated environments Ability to explain analytical approaches clearly to non-technical stakeholders  

Preferred Qualifications, Capabilities and Skills: 

Exposure to Generative AI use cases for automation, documentation, or workflow efficiency Familiarity with SQL for querying large datasets  Experience with Apache Spark for distributed data processing Familiarity with Databricks or similar cloud-based analytics platforms Exposure to machine learning concepts or frameworks, particularly as they relate to anomaly detection or classification  Experience documenting analytical methodologies for audit, risk, or regulatory review 

 

This position is not eligible for visa sponsorship. 

This position is in-office 5 days a week.