Applied AI/ML - Senior Associate
On-site · New York City, New York, United States
Job Summary
Senior Associate Applied AI/ML Scientist in the JP Morgan Payments division. You will research, experiment, and deploy machine learning models, services, and platforms to streamline payment processes, bolster fraud detection, and enhance customer experience. You will design scalable data processing pipelines, perform analysis to derive business impact, and collaborate with Product, Technology, Risk, and Compliance teams to ensure model documentation and regulatory adherence. You will translate model outcomes into actionable business metrics and communicate insights to senior management, while driving production-ready ML capabilities and applying NLP/LLM techniques alongside traditional ML approaches.
Required Qualifications
- Master’s degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research) with a minimum of 3 years of industry experience
- Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services
- 2+ years of hands-on experience with large-scale data processing on AWS EMR, building batched feature stores (offline/online pipelines, schema governance, backfills, reproducibility), and orchestrating SageMaker training, pipelines, and model registry for production ML
- Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (TensorFlow, PyTorch) and libraries (NumPy, Scikit-Learn, Pandas)
- 1+ years of extensive experience in NLP or LLMs, AgenticAI, and 3+ years in other ML techniques (classification, regression)
- Solid understanding of ML/AI algorithms including LLMs and Generative AI; familiarity with state-of-the-art practices
- Proficient in exploratory data analysis (EDA) and understanding of methodologies' limitations
- Ability to transform vague business questions into structured analytical plans and strong communication skills
- Experience in the financial services industry is a plus (preferred)
- Cloud computing: AWS, Azure, Docker, Kubernetes, DataBricks, Snowflake
- Trust & Safety fraud experience in payments (preferred)
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