below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$145,200–$213,817.
Based on 240 similar postings.
Employer
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.
JPMorgan Chase currently has
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
The Applied AI & Data Product Scientist joins the Finance Transformation and Analytics team as a Vice President to architect next-generation AI-driven analytics and decision-support products. This individual contributor role involves spending sixty percent of the time hands-on building and forty percent shaping strategy. Key responsibilities include researching and prototyping agentic workflows, multi-agent orchestration, and retrieval-augmented generation while diagnosing structural data problems. The candidate will write code, train models, and design data architectures to remediate data quality gaps and establish semantic data layers. Required skills include Python, SQL, and experience with large language models, vector stores, and cloud platforms like AWS, Snowflake, or Databricks. The role solves complex data problems within asset and wealth management finance, specifically focusing on financial planning, forecasting, and management reporting.
Research and prototype emerging AI capabilities like agentic workflows and RAG into production-grade products.
Architect and scale large language model agents integrated with APIs, microservices, and cloud platforms.
Design evaluation harnesses, guardrails, and human-in-the-loop review processes for all AI products.
Audit and remediate data quality and lineage gaps to establish a single source of truth.
Architect curated semantic data layers that are consistent and reusable across all reporting and AI products.
Establish data observability practices including monitoring, alerting, and lineage tracking.
Define and own a forward-looking AI and data roadmap aligned with Finance priorities.
Design experimentation frameworks to quantify the business impact of AI products and data improvements.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, Finance, or a related quantitative field.
8 years of experience in data science, AI/ML, analytics, or product engineering with hands-on delivery of production AI or ML applications.
Hands-on experience with large language models including prompt engineering, retrieval-augmented generation, function calling, embeddings, vector stores, and evaluation frameworks.
Strong Python and SQL fluency with experience building and operating production data and inference pipelines end-to-end.
Practical expertise with cloud data platforms such as AWS, Snowflake, or Databricks, including distributed processing and data modeling.
Demonstrated ability to take AI or generative AI solutions from concept through prototype to scaled production.
Experience diagnosing and fixing data quality, lineage, and governance problems in complex enterprise environments.
Understanding of Finance functions such as financial planning and analysis, management reporting, forecasting, and KPI frameworks within financial services.
Generative AI
Machine Learning
Natural Language Processing
Large Language Models
Python
SQL
LangChain
DSPy
MLOps
Data Science
Multi-objective Optimization
Real-World Data
Data Visualization
Business Intelligence
Database Management