Chief Data Office - Data Quality - Business Analytics Associate

Job Description — Senior Associate, Business Analytics (Chief Data Office, CIB)

Role Summary

The Chief Data Office (CDO) within the JPMorganChase Commercial & Investment Bank (CIB) is seeking a Senior Associate to support high-priority CIB initiatives focused on increasing quality of Sales’ data for the Markets business. This role is project-driven (little fixed BAU), requires strong analytical problem-solving, and will partner closely with business, product, and technology stakeholders to identify data quality issues, size impact, and drive resolution paths from discovery through remediation.

Key Responsibilities

• Deliver analytics for high-priority CIB programs, per the Sales CDO’s strategy, with a focus on improving the quality and usability of data used by Markets Sales.
• Perform data quality assessments (profiling, anomaly detection, reconciliation, completeness/accuracy/timeliness checks) and quantify business impact.
• Lead issue triage and resolution planning: document findings, identify root causes, propose remediation options, and define/track resolution paths with owners.
• Build and maintain repeatable workflows for data preparation and analysis.
• Develop dashboards and reporting to monitor data quality metrics, remediation progress, and key outcomes for senior stakeholders.
• Partner cross-functionally with CIB stakeholders (product teams, data owners, tech teams, control/operational partners as applicable) to align on definitions, requirements, and prioritization.
• Improve documentation and controls: data dictionaries, business rules, issue logs, and operational runbooks for project deliverables.

Required Qualifications

• Bachelor’s degree or equivalent practical experience.
• Strong experience in business analytics / data analytics roles (typically 5+ years, or equivalent depth).
• Hands-on capability with: 
  • Alteryx (automating analytics workflows, data blending, validation)
  • Dashboarding (e.g., Tableau, Power BI, or similar—building stakeholder-ready views and KPIs)
  • SQL / Python (data extraction, cleaning, analysis, automation; ability to productionize analytics where appropriate)
  • AI-enabled improvement experience demonstrated ability to apply AI/ML and generative AI techniques to reduce manual effort, accelerate data analysis, and improve decision making
• Demonstrated ability to work in ambiguous, project-based environments with shifting priorities and tight timelines.
• Strong stakeholder management and communication skills, including writing clear issue narratives and presenting insights to non-technical audiences. 
• Proven experience identifying data quality issues and driving structured remediation with accountable owners.

Preferred / Nice-to-Have 

• Experience with data quality tooling (e.g., Informatica, Collibra or similar DQ/profiling platforms).
• Familiarity with data governance concepts (critical data elements, lineage, controls, metadata, stewardship).
• Experience working with Client/Sales/CRM-type datasets (contacts, coverage, relationship hierarchies, Core Reference data) and associated quality challenges.
• Comfort working across large enterprise data ecosystems and collaborating with data and engineering teams.

Competencies

• Analytical rigor and curiosity; strong hypothesis-driven problem solving
• Strong attention to detail; comfort with imperfect data
• Ability to translate business problems into data tests and measurable metrics
• Self-starter, able to work autonomously, with strong time management skills; efficient at multi-tasking and able to work under pressure to deliver multiple business demands on-time, to a high standard
• Excellent communication, presentation (both oral and written) & influencing skills - candidate will be dealing with stakeholders of varying degrees of seniority