We are seeking a talented, ambitious Associate with a passion for data analytics and machine learning to join our team of professionals driving product insights and recommendations to our front office Banking and Payments teams in Global Banking.
As an Associate within our organization, you will be directly accountable for building and maintaining powerful data models and agentic (LLM-enabled) solutions that enable JPMorganChase global bankers to identify new opportunities for their clients and prospects and win new business. You will work across a team of business representatives, product managers, and data scientists to harness JPMorganChase’s vast internal and external data sources to design and implement advanced analytics and AI/ML models—delivering an always-on feed of insights and client analytics that drive increased revenues, time savings, and improved client outcomes. You will design and build solutions directly with end users, and when a solution is ready to be deployed, you will partner with our data engineering, applied ML, and MLOps teams to productionize, monitor, and scale it.
Job responsibilities
- Maintain and enhance an existing suite of models that drive live insights and product recommendations to bankers
- Design, build, and maintain analytics data products (reliable datasets, attributes, and metrics) that power ML models and banker-facing insights
- Create ML/SQL models from payments data to identify product usage behaviors, competitor/supplier trends, and key events
- Build agentic (LLM-enabled) workflows on top of our data ecosystem to help our banking teams act on insights efficiently and consistently
- Manage product performance and model quality metrics (product adoption, influenced meetings, new sales, and model performance over time)
- Participate in user feedback sessions to engage with the business on enhancements, validate prototypes, and generate new ideas
- Partner with tech engineering, data engineering, applied ML, and MLOps teams to plan, prioritize, deploy, and monitor models and agents into production
Required qualifications, capabilities and skills
- Advanced SQL and/or Python skills, with experience launching analytics and/or AI/ML models and features into production
- Experience working with AWS platform/programming tools such as Databricks (or similar distributed data processing platforms)
- Experience with feature engineering, model evaluation, and production monitoring (e.g., drift, performance, and data quality)
- Familiarity with LLM/RAG patterns and agentic workflows, including practical evaluation approaches
- Experience in financial services, big data, technology, or relevant start up environment
- Bachelor’s or master’s degree in business/data analytics, math, statistics, engineering, or a related field
- Business acumen to effectively work with non-technical business partners and leaders; ability to translate business needs into data/ML solutions