VP AI/ML Data Scientist

JPMorgan Chase & Co.
United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

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
+22 more
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

Job 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.

Requirements

  • 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.

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

About the company

JPMorganChase, 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 processing and asset management.

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