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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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Internal Audit, Asset Wealth Management - Senior Associate - Data Scientist joins the Audit Analytics team to deliver end-to-end data science and analytics solutions across the audit lifecycle. This role involves translating audit objectives into actionable insights, engineering scalable code modules, and developing automated workflows for continuous monitoring and risk-based scoping. The individual will manage data acquisition, modeling, and visualization while ensuring all outputs meet rigorous governance and quality control standards. Key technical tools include SQL, Python, Alteryx, Databricks, Tableau, Agentic Studio, and Smart SDK. Candidates must possess expertise in handling large datasets, ETL patterns, and API integration to solve complex risk management problems. The role requires strong communication skills to explain technical concepts to non-technical audiences while building repeatable solutions that enhance audit efficiency and support informed decision-making within the asset and wealth management domain.
What does a Data Scientist earn?
Median $162000 from 295 postings across 61 companies.
Deliver end-to-end analytics and data science solutions using SQL, Python, Alteryx, and Databricks across the audit lifecycle.
Translate audit objectives into actionable analytic hypotheses and test designs to support risk-based scoping.
Engineer scalable, repeatable solutions including reusable code modules, automated workflows, and dashboards for auditor self-service.
Develop advanced testing solutions such as continuous monitoring, automated testing, and event-based analytics.
Apply data management and governance practices to ensure all analytic outputs are reliable, auditable, and reproducible.
Implement quality controls including validation checks, reasonableness testing, and detailed documentation for all analytical outputs.
Communicate complex technical findings and insights to non-technical stakeholders through tailored messaging and visualizations.
Evaluate and adopt new tools and techniques to improve team efficiency and recommend process enhancements.
What we're looking for
Bachelor's degree in Computer Science, Data Analytics, Data Science, Information Systems, Engineering, or a related discipline (or equivalent practical experience).
Minimum 3 years of experience in Audit, Data Analytics, Data Science, Risk/Controls, or a closely related role.
Experience working with large, complex datasets including data wrangling, validation, enrichment, and building analytics solutions.
Proven track record of delivering repeatable, production-ready data science solutions such as automated workflows, dashboards, or model development.
Strong understanding of data ecosystems, including databases, warehouses/lakes, ETL/ELT patterns, and how technology design impacts risk and auditability.
Working knowledge of data management principles including quality, lineage, metadata, governance, and documentation practices for reproducibility.
Excellent communication skills to explain technical concepts to non-technical audiences and build partnerships.
Experience with cloud platforms (Databricks, Snowflake), visualization tools (Tableau), or agentic tooling (Agentic Studio, Smart SDK) (preferred).