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JPMorganChase

Quant Analytics Senior Associate

Posted 2 Hours Ago
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Remote or Hybrid
2 Locations
Senior level
Remote or Hybrid
2 Locations
Senior level
Designs and maintains governed, analytically ready datasets for AML/KYC operations. Builds scalable ETL and transformation processes using SQL and Python, develops metadata and semantic layers for AI and self-service analytics, and implements data quality, reconciliation, and validation frameworks. Partners with operations, data, technology, and AI teams while supporting production data assets, documenting findings, addressing source-system impacts, and ensuring compliance with controls, privacy, and regulatory standards.
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At JPMorganChase, we are seeking team members who are eager to modernize how data is used to identify financial crime risk and improve customer due diligence outcomes. As a Quant Analytics Associate Sr within the Data & Analytics organization supporting AML/KYC operations, you will help move the team beyond traditional Excel-based, retrospective reporting toward proactive and scalable analytical solutions that identify emerging risks, data quality issues, process gaps, and customer trends earlier in the case lifecycle.

In this role, you will focus on designing, building, and maintaining analytically ready datasets that can be used by analysts, operational stakeholders, AI agents, and natural-language query tools. You will partner closely with AML/KYC operations, product owners, data owners, technology teams, and other analytics professionals to transform customer, transaction, and activity data into governed, well-documented, AI-ready data assets.

The successful candidate will bring strong SQL expertise, practical ETL experience, comfort with Python, curiosity about AI-assisted code creation, and a strong ability to independently investigate ambiguous data problems. This role is ideal for someone who wants to combine hands-on data engineering, analytics, controls awareness, and business problem solving to help modernize AML/KYC decision support.

Job Responsibilities:

  • Design, develop, and maintain analytically ready datasets for AML/KYC operations, including datasets that support proactive monitoring, case prioritization, customer review insights, trend detection, and data quality surveillance.

  • Build scalable ETL and data transformation processes that convert raw source-system data into reliable, well-structured, reusable data products for the broader Data & Analytics team.

  • Develop AI-ready metadata, business definitions, lineage documentation, data dictionaries, and semantic layers that enable AI agents, self-service analytics, and natural-language querying.

  • Use Python/SQL as the primary tool for data extraction, transformation, profiling, validation, and performance optimization across large and complex datasets.

  • Apply Python and AI-assisted code generation tools to improve development speed, automate repetitive analytics tasks, create reusable utilities, and support exploratory data analysis.

  • Collaborate with analytics and AI teams to ensure datasets are structured for downstream model development, AI-agent orchestration, retrieval-augmented workflows, and natural-language business questions.

  • Create data quality checks, reconciliation routines, exception monitoring, and validation frameworks to ensure ARDs are accurate, complete, timely, and fit for purpose.

  • Prepare clear documentation and executive-ready presentations summarizing data findings, ARD readiness, development progress, data quality risks, and recommended next steps.

  • Provide ongoing production support for data assets, including troubleshooting data issues, answering stakeholder questions, managing enhancements, and communicating impacts of source-system changes.

  • Ensure analytics, data transformation, and AI-enablement activities comply with applicable controls, model/data governance expectations, privacy requirements, and regulatory standards.

  • Contribute to a culture of innovation by proposing new approaches for data modernization, metadata enrichment, AI enablement, and proactive risk identification.

     

Required Qualifications, Skills and Capabilities:

  • 3+ years of related experience.
  • Bachelor's degree in a quantitative or related field required; Master’s degree preferred.
  • Excellent critical thinking and problem-solving abilities.

  • Proficiency in SQL and Python.
  • Experience with Alteryx and Tableau preferred.
  • Knowledge on how to integrate with APIs preferred.
  • Strong project management skills with the ability to manage multiple projects simultaneously.
  • Familiarity with data mining, statistical modeling, machine learning, and other advanced analytics methods.
  • Robust data management skills with a focus on ensuring data quality and organization.
  • Demonstrated ability to independently make the decisions and judgements necessary to deliver quality analytics solutions.
  • Effective communication skills, both written and verbal.
  • Strong soft skills, including adaptability, emotional intelligence, and conflict resolution.
  • Strong adherence to controls and regulatory requirements.
  • Commitment to continuous learning and professional development.
About Us

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

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. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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