Applied AI/ML Scientist – Payments Solutions

Testing Site - JPMC; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

J.P. Morgan Payments is seeking an Associate Applied AI/ML Scientist to advance payment solutions with state‑of‑the‑art AI/ML models and scalable data pipelines.

You will research, develop, and productionize models to improve fraud detection, processing speed, and customer experience while partnering with cross‑functional teams. The role emphasizes translating complex model outcomes into business impact, adhering to regulatory requirements, and delivering data‑driven outcomes across borders and

Qualifications

• Bachelor’s degree in a quantitative field and 3+ years of industry experience in AI/ML.
• Proficiency in Python with hands-on experience in ML/DL frameworks and libraries.
• Experience with NLP/LLM or CV and related ML techniques; strong data analysis and EDA skills.

Responsibilities

• Collaborate with Product and Technology teams to translate business problems into data-driven AI/ML solutions.
• Design, develop, and deploy ML/AI models and services with attention to scalability and latency.
• Ensure model documentation and regulatory compliance in partnership with Risk and Compliance.
• Translate model outcomes into business impact metrics for senior stakeholders.

Skills

Python

Machine learning

Deep learning

NLP / LLM

Analytical thinking

Data analysis

Education

Bachelor's degree in Computer Science / Data Science / Mathematics

Tools

AWS Cloud Services

TensorFlow

PyTorch

NumPy

Pandas

Scikit-Learn

SQL

Jupyter Notebook/Lab

Docker

Kubernetes

Job description

J.P. Morgan Payments is seeking an Associate Applied AI/ML Scientist to advance payment solutions with state‑of‑the‑art AI/ML models and scalable data pipelines.

You will research, develop, and productionize models to improve fraud detection, processing speed, and customer experience while partnering with cross‑functional teams. The role emphasizes translating complex model outcomes into business impact, adhering to regulatory requirements, and delivering data‑driven outcomes across borders and