
Data Scientist AI Operations-Senior Associate
at J.P. Morgan
Posted 12 days ago
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- Compensation
- Not specified
- City
- Not specified
- Country
- United States
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Data Scientist on the AI/ML for Ops Data Team responsible for making data AI-ready using AI/ML techniques. Design and demonstrate POCs to make structured and unstructured data AI-ready, building and iterating prototype solutions with Python, LLMs, and AI vendor tools. Partner with subject matter experts and collaborate with Engineering and Data Science to productionize POCs and optimize data for AIML solutions. Analyze diverse data assets to derive insights and actionable recommendations for sequencing.
Location: Jersey City, NJ, United States
Are you passionate about leveraging artificial intelligence and machine learning solutions to solve real-world problems?
As a Data Scientist on the AI/ML for Ops Data Team , you'll leverage AI and ML to make data AI-ready. You’ll use your expertise with Large Language Models, predictive models, and generative AI solutions with the Consumer and Community Bank Operations Data Owner team.
Job Responsibilities:
- Use your programming skills in Python and design integrated solutions for AI-readiness of data. Leverage python libraries, LLMs, and vendor solutions to enable seamless integration of AIML models with business data needs.
- Design and demonstrate POCs for making structured and unstructured data AI-ready. Build and iterate on prototype solutions.
- Partner with subject matter experts and help deliver solutions that optimize the data for AIML solutions.
- Closely collaborate with Engineering and Data Science to productionalize your POCs.
- Analyze diverse data assets and sources to prioritize, developing insights that lead to actionable recommendations for sequencing.
Required qualifications, capabilities and skills:
- Degree in quantitative discipline (e.g., Computer Science, Mathematics, Operations Research, Data Science).
- 3+ years' experience in creating predictive models, and generative AI solutions using LLM prompt engineering, Retrieval Augmented Generation (RAG).
- Strong Proficiency in Python.
- Hands-on experience with LLM APIs, Python libraries like Pandas, NumPy, scikit-learn, and others for data manipulation, modeling and analysis.
- Proficiency with data table operations (SQL, etc.).
- Experience designing, building and maintaining ETL data pipelines using tools such as SQL, Python, and Alteryx.
- Experience with evaluation metrics for ML and generative AI, and with building monitoring dashboards.





