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