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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # VP AI/ML Data Scientist - **Company:** JPMorgan Chase & Co. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Automation of Tests, Network Analysis, Cloud Computing, Continuous Integration, Data Governance, Data Mining, Data Profiling, Data Warehousing, Graph Database, Python (Programming Language), NumPy, Cloud Services, Tensorflow, Software Deployment, Software Engineering, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Model Validation, Pandas, Containerization, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Software Version Control - **Published:** May 13, 2026 - **Apply:** https://www.dice.com/job-detail/d48e84db-e26d-4b83-b51f-0f15d095caa0 ## About the Role * 7-10+ years building and deploying ML models in production, ideally in banking, payments, or similarly regulated domains. * Strong Python & SQL; proficiency with pandas, NumPy, scikit-learn, XGBoost, and at least one deep learning framework (PyTorch or TensorFlow); solid software engineering practices. * MLOps experience: containerization/orchestration, experiment tracking, model registries, monitoring, drift detection, and structured change management. * Cloud fluency: AWS services (EKS, EC2, Lambda), distributed query engines, and data warehousing. * Stakeholder management: proven ability to translate banking workflows and commercial objectives into technical requirements; strong communication across front office, Product, risk, compliance, and technology. * Data governance awareness: familiarity with KYC/AML context and model risk frameworks., * Experience supporting Global Banking & Payments and COS stakeholders. * Hands-on with LLMs and agentic systems: RAG, structured outputs, tool use, guardrails/safety, and evaluation frameworks. * Experience with graph analytics, NLP, and time-series modeling for prospecting, network analysis, and forecasting. * Familiarity with feature stores, A/B testing, and performance/cost optimization at scale. * Advanced degree in a quantitative field (Computer Science, Statistics, Mathematics, Engineering, or quantitative Finance/Economics) or equivalent experience. ## Description As a VP AI/ML Data Scientist in CIB's Global Banking & Payments group, you will translate complex banking challenges into scalable, production-grade AI/ML and LLM solutions. Partnering with stakeholders across Global Banking & Payments, front office, Product, and Client Onboarding & Service (COS), you'll build prototypes and deliver governed models and intelligent agents that improve origination velocity, revenue quality, client engagement, operational efficiency, and risk reduction., * Define & deliver high-value use cases with Global Banking & Payments stakeholders - prospecting and wallet-share models, fee/revenue forecasting, deal probability, investor/counterparty mapping, onboarding triage, service case routing, and execution analytics. * Build COS Agents to automate Client Onboarding & Service workflows - document intake/QC, KYC data extraction, case summarization, and multi-step resolution. * Develop LLM solutions using retrieval-augmented generation, agent orchestration, prompt engineering, guardrails, and red-teaming to deliver reliable, explainable outcomes. * Own end-to-end pipelines: data profiling, feature engineering, model development, evaluation, fairness/explainability, and production deployment in cloud and hybrid environments. * Implement MLOps: version control, model registry, CI/CD, containerization, automated testing, monitoring, drift detection, and incident/rollback procedures. * Leverage cloud data platforms: AWS (EKS, EC2, Lambda), query engines (Starburst/Trino), data warehouses (Redshift), and graph databases (Neptune). * Ensure governance & compliance - enforce data access controls, privacy requirements, secure compute, and lineage throughout the model lifecycle. * Drive adoption: run A/B tests, capture user feedback, mentor junior team members, and champion responsible AI practices., J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. ## Related Videos - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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