About The Position

As a Data Owner within JPMorganChase’s Wholesale Credit Risk Product team in Risk Management and Compliance, you will collaborate with technology partners, subject matter experts, and stakeholders to develop and implement a comprehensive data strategy. You will ensure data integrity, quality, and accessibility across credit risk processes and applications, defining critical data elements, standardizing operating models, and driving automation and data quality improvements. The role supports delivery of trusted, well-governed data for effective credit risk decision-making.

Requirements

  • Bachelor’s degree in a relevant field.
  • 5 years plus of relevant experience in credit risk, data strategy, data management, or a related capacity.
  • Strong written and verbal communication skills, including executive-level communications.
  • Excellent organizational skills and attention to detail, with the ability to manage competing priorities under tight deadlines.
  • Proven ability to collaborate and build strong partnerships.
  • Intellectual curiosity and a proven ability to learn quickly.
  • High degree of initiative, self-direction, and ability to work well under pressure.
  • Strong data analysis, problem-solving, and project management skills.
  • Demonstrated experience leading cross-functional data initiatives with multiple stakeholders.
  • Ability to lead, drive consensus, and deliver in a matrix organization.
  • Experience using data and metrics to drive decisions, with proficiency in process re-engineering or similar disciplines.

Nice To Haves

  • Experience within large financial services firms with basic domain knowledge in credit risk.
  • Experience working with Technology and UX Design colleagues and discussing technical designs.

Responsibilities

  • Define critical data elements across credit risk processes and applications.
  • Build and maintain data dictionaries with standardized business definitions.
  • Define ownership of data inputs, enrichment, changes, and outputs across processes.
  • Standardize data operating models for inputs and enrichment to achieve consistency across lines of business.
  • Identify and define strategic sources of data.
  • Identify data automation opportunities using systemic feeds, large language models, and agents, automating data enrichment where possible.
  • Define schemas for data assets and publish data lineage across inputs, enrichment, and outputs.
  • Establish a robust business and technical data quality program to ensure data is fit for use.
  • Establish and monitor data-level key performance indicators across products.
  • Implement continuous data testing and refinement, using anomaly detection where possible.
  • Address and remediate regulatory requirements in collaboration with individual product teams.
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