Data Analyst Payments Analytics - Vice President

JPMorgan Chase & Co.; Plano (TX); On-site; USD 85,000 - 125,000; Full time

Job summary

JPMorgan Chase & Co. in Plano, TX seeks a Data Analyst in SMB Payments to elevate analytics, strengthen reporting, and design AI-augmented analytics that illuminate partner and merchant behavior and outcomes.

You will identify key metrics, build durable reporting, and conduct analyses to inform business strategies, collaborating with Product, Sales, Marketing, Account Management, and Risk to drive upsell and cross-sell initiatives while applying GenAI thoughtfully to unlock insights from

Qualifications

• 5+ years of experience in analytics delivering business-critical insights and reporting.
• Fluency in SQL and Python for analysis, automation, and reproducible analytics.
• Experience building dashboards and visualizations (Tableau or BI tools).
• Knowledge of AI/LLM concepts and practical use cases.
• Strong collaboration across Product, Sales, Marketing, Risk.

Responsibilities

• Identify, define, and maintain core SMB Payments performance metrics; build scorecards/dashboards and recurring reporting for stakeholders.
• Perform deep-dive analyses to surface trends, drivers, and root causes; translate findings into clear narratives and recommended actions.
• Build scalable datasets and self-service analytics assets with clear documentation (metric definitions, assumptions, and data lineage).
• Partner with Product and commercial teams to size opportunities, monitor funnel performance, and measure outcomes of upsell/cross-sell initiatives.
• Apply LLMs and modern AI techniques to augment analytics workflows and reduce time-to-insight.
• Help design and run LLM evaluation and monitoring and contribute to improving prompts, retrieval approaches, and end-to-end performance.
• Use critical thinking and advanced analytics to diagnose underperforming models/pipelines, data issues, drift, and prompt Failures.
• Collaborate with partners across Product, Engineering, Data, and Risk to ensure AI-enabled solutions are secure, compliant, auditable, and reliable in production.

Skills

5+ years analytics experience

Cross-functional collaboration

Data storytelling

Education

Bachelor’s degree in CS/Statistics/Economics/Mathematics/Engineering

Tools

SQL

Python

Tableau/BI tools

Job description

We are seeking aData Analystto elevate our analytics capabilities, strengthen core reporting, and help design and operationalizeAI-augmented analyticsthat improve how we understand partner and merchant behavior and outcomes.

As a Data Analyst in SMB Payments , you will play a pivotal role in identifying key metrics, building durable reporting, and conducting comprehensive analyses to inform business strategies. You will work collaboratively with cross-functional teams—includingProduct, Sales, Marketing, Account Management, and Risk—to drive product upselling and cross-selling, enhancing both partner and merchant experiences.You will also contribute to the team’sLLM/AI analytics roadmapby applying GenAI thoughtfully to unlock insights from unstructured and semi-structured data (e.g., call notes, tickets, feedback, emails where permitted), automate narrative generation, and improve analytic workflows—while ensuring strong controls, data privacy, and measurable quality.

TheJPMorganChase SMB Payments Analyticsteam is dedicated to cultivating a data-driven culture and empowering fact-based decision-making. Our Business Analytics division champions this mission by delivering data, insights, and scalable reporting—while also accelerating the integration of modern analytics techniques, includingLLM/GenAI-enabled insights, into everyday decisioning.

Job Responsibilities

• Identify, define, and maintaincore SMB Payments performance metrics; build scorecards/dashboards and recurring reporting for stakeholders.
• Perform deep-dive analyses to surface trends, drivers, and root causes; translate findings into clear narratives and recommended actions.
• Build scalable datasets and self-service analytics assets with clear documentation (metric definitions, assumptions, and data lineage).
• Partner with Product and commercial teams to size opportunities, monitor funnel performance, and measure outcomes of upsell/cross-sell initiatives.
• ApplyLLMs and modern AI techniquesto augment analytics workflows (e.g., summarization, topic modeling/classification, semantic search, insight extraction) and reduce time-to-insight.
• Help design and runLLM evaluation and monitoring(quality, robustness, latency, cost) and contribute to improving prompts, retrieval approaches, and end-to-end performance.
• Use critical thinking and advanced analytics to diagnoseunderperforming models/pipelines(data issues, drift, prompt failures, weak retrieval, label quality).
• Collaborate with partners across Product, Engineering, Data, and Risk to ensure AI-enabled solutions aresecure, compliant, auditable, and reliablein production.

Required Qualifications, Capabilities, and Skills

• 5+ years of experience in analytics, business analytics, or data analysis delivering business-critical insights and reporting.
• Fluency inSQLandPythonfor analysis, automation, and reproducible analytics.
• Strong ability to frame ambiguous business problems, design analyses, and communicate results to both technical and non-technical audiences.
• Experience building dashboards and visualizations (e.g.,Tableau; other BI tools acceptable).
• Demonstrated exposure toAI/LLM concepts and applied use cases(prompting/evaluation, embeddings/semantic search, text analytics, or ML experimentation) with a strong interest in expanding hands-on delivery.
• Strong collaboration skills across cross-functional stakeholders (Product, Sales, Marketing, Account Management, Risk).

Preferred Qualifications, Capabilities, and Skills

• Bachelor’s degree (Master’s a plus) in Computer Science, Statistics, Economics, Mathematics, Engineering, or related field (or equivalent experience).
• Knowledgeofconsumer/retail banking and/or payments products(SMB/payments domain strongly preferred).
• Working knowledgeofAlteryxand advanced Tableau development.
• Experience with big data and modern data ecosystems (e.g., Spark, cloud data platforms, distributed querying).
• Experience with ML/AI tooling (e.g., scikit-learn, PyTorch/TensorFlow) and/or deploying analytics into production workflows.