Data Scientist Senior Associate — Business Observability & AI Platform

Join a fast-moving technology team building a business observability platform for the Payments business—an analytics foundation that enables AI-assisted decision-making for senior leaders and real-time monitoring and alerting for operations teams. You’ll help deliver intraday transaction insights, anomaly detection, forecasting, and conversational analytics supported by a governed metrics foundation.

As a Data Scientist Senior Associate at JPMorgan

Chase within Business Observability & AI Platform in Payments
, you will own the analytical integrity of what we ship. You will validate the data behind key metrics, define what “correct” looks like for models, and ensure anomaly detection and forecasting outputs remain trustworthy in production. You will partner closely with product, engineering, and design to shape both the roadmap and how we communicate value to stakeholders.

• Perform exploratory and diagnostic data analysis across large-scale transactional datasets to validate business logic, metric definitions, and data quality
• Define and document acceptance criteria for analytical features, metrics, and model behavior; verify releases against them before sign-off
• Design and run validation and back-testing for anomaly detection and forecasting models, including accuracy, precision/recall, false-positive rates, and threshold calibration
• Build and operate model and data drift monitoring, and recommend retraining or recalibration when performance degrades
• Investigate and triage analytical defects, reconciliation breaks, and unexpected model output with upstream data and platform teams
• Create clear data visualizations and analytical narratives for executive and operational audiences, and contribute to product demos and stakeholder materials
• Partner with the Technical Product Owner on requirements, user story refinement, and prioritization grounded in evidence from the data

• Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar)
• 2+ years of applied data analysis or data science experience, or an advanced degree with relevant internship/project work
• Strong SQL, including analytical functions and performance-aware querying against large tables
• Proficiency in Python and the standard analytics stack (pandas, Num Py, scikit-learn, stats models or equivalent)
• Working knowledge of time series analysis, forecasting methods, and anomaly detection techniques`Professional experience with data quality testing, validation frameworks, and reconciliation
• Ability to build clear, decision-ready visualizations and communicate findings to non-technical stakeholders
• Comfortable working in an agile, high-ownership environment with shifting priorities

• Experience with payments, transaction banking, or financial services data
• Familiarity with semantic layers, metrics stores, or dimensional modeling
• Exposure to columnar or OLAP databases (Click House, Druid, Big Query, Snowflake)
• Experience defining model evaluation and drift monitoring in production
• Familiarity with LLM-assisted analytics, evaluation of generated explanations, or prompt-based workflows
• Visualization tooling beyond notebooks (D3, Plotly, Tableau, or similar)

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JPMorgan

Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction…