Applied AI/ML Senior Associate - Payments
On-site · New York City, New York, United States
New York City, New York, United StatesOn-siteFull TimeSenior LevelMasters DegreeFinancial ServicesEnterprise
Type
Full Time
Level
Senior Level
Education
Masters Degree
Company size
Enterprise
Industry
Financial Services
Job Summary
Sr. Associate Applied AI/ML Scientist in JP Morgan Payments responsible for researching, developing, and deploying ML/AI solutions to enhance payment processes, bolster fraud detection, and improve customer experience. Design and operate scalable data processing pipelines, collaborate with Product/Tech and Risk & Compliance to document models and ensure regulatory adherence, translate model outcomes into business impact, and communicate findings to senior management.
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 robust 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). Experience with Jupyter Notebook/Lab is essential
- 1+ years of extensive experience in NLP or Large Language Models (LLM), AgenticAI, and 3+ years in other machine learning techniques (classification, regression)
- Strong hands-on expertise in neural networks and Transformers, including practical experience with Fine-tuning strategies
- Experience building data-driven systems using SQL and distributed processing (e.g., Spark/PySpark)
- Solid understanding of algorithms in machine learning, AI, and neural networks, including LLMs and Generative AI, plus familiarity with state-of-the-art practices
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