Chief Data Office - Data Quality - Business Analytics Associate

JPMorgan Chase · ✓ Verified company
📍 Mumbai, Maharashtra, India · On-site · Full-time

About the role

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