Data Scientist - Applied AI/ML

JOB DESCRIPTION

Join a world-class Applied AI/ML organization at JPMorganChase and help shape how teams across the firm use data science, machine learning, and Generative AI to solve real business problems.

As a Senior Associate in Applied Artificial Intelligence and Machine Learning within Shared Services, you design and deploy predictive models, advanced analytics, and large language model agentic solutions that orchestrate tools and workflows inside business processes. You wil build reusable services that teams can adopt to improve risk assessment support, legal and regulatory change mapping, control design and testing, sustainable monitoring, issue tracking, and governance reporting.

Job Responsibilities

Design, develop, and deploy predictive machine learning, advanced analytics, and generative AI solutions for complex business problems

Build and integrate agentic workflows into end-to-end business processes, including retrieval-augmented generation, tool or function calling, routing, and structured outputs

Prototype AI-enabled approaches quickly and harden successful prototypes into reusable, production-ready services with measurable outcomes

Own end-to-end model delivery, including dataset preparation, feature engineering, training, validation, evaluation, deployment, and iteration

Design, deploy, and operate production pipelines and services (batch and real-time), including monitoring, retraining strategies, and reliability and cost improvements

Partner with product, engineering, and risk and controls stakeholders to define requirements, align on success metrics, and drive adoption

Apply responsible AI and governance-aligned practices across the model and agent lifecycle, including evaluation, guardrails, and documentation

Contribute reusable patterns, templates, and libraries that accelerate delivery across teams

Required qualifications, capabilities, and skills

Bachelor's degree in data science, computer science, statistics, mathematics, or a related technical field (or equivalent practical experience)

Three years of experience delivering end-to-end AI or machine learning solutions from prototype to production (or production-like) deployment

Strong Python proficiency for data analysis, modeling, and production implementation

Experience building, evaluating, and deploying predictive models (for example, classification, regression, or natural language processing) using common libraries (for example, PyTorch, TensorFlow, or scikit-learn)

Experience building and deploying large language model workflows that include retrieval-augmented generation and tool or function calling

Experience defining and using an evaluation approach for large language model solutions (for example, test sets, regression tests, or structured human review)

Experience operating production pipelines or services, including versioning, continuous delivery practices, monitoring and alerting, and incident hygiene

Working knowledge of cloud and or containerized environments (for example, Amazon Web Services, Microsoft Azure, Google Cloud Platform, or Kubernetes)

Strong communication skills, including the ability to translate business problems into measurable technical outcomes and explain results to diverse audiences

Preferred qualifications, capabilities, and skills

Master's degree or doctorate in a quantitative field

Publications, patents, or meaningful open-source contributions related to machine learning or generative AI

Experience scaling agentic systems across multiple use cases, including mature evaluation practices and quality dashboards

Experience implementing guardrail patterns and operating controls for generative AI features in production

Experience with large-scale data processing and cloud data services, and exposure to performance optimization for model serving

Experience in financial services or other regulated industries, including comfort operating within governance and change management expectations

Experience with specialized domains such as search and ranking, recommender systems, graph machine learning, or knowledge graphs

ABOUT US

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.

ABOUT THE TEAM

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.