Join the Cards Data & Analytics team at JPMorgan Chase, where we leverage data science, research, and business acumen to deliver impactful solutions.
As a Data Scientist Senior Associate within the Co-Brand Card Analytics team, you will be responsible to lead projects that integrate agentic workflows, business intelligence platforms, and advanced analytics solutions. You will own end-to-end delivery of segmentation models, strategic analyses, and AI-driven insights that inform partnership strategies and portfolio decisions. Utilizing tools such as Databricks, Python, Tableau and Alteryx, you will develop data pipelines and dashboards, prototype AI-driven solutions, and translate complex data into strategic recommendations for Co-Brand business partners.
Job Responsibilities
- Be part of the Segmentation and Strategic Analytics team and drive analytics-driven business strategy and growth for Co-Brand Card partnerships. Learn our business and how JPMorgan delivers value for our customers and partners through Co-Brand credit card products.
- Leverage your technical skillset, domain expertise, and curiosity to identify opportunities to help grow our Co-Brand Cards business through advanced segmentation and strategic analytics.
- Build and rigorously test new data and AI driven insights, owning the end-to-end analytical lifecycle from hypothesis to production-ready deliverables.
- Develop scalable frameworks for seamless AI model integration across business applications. Ensure solutions can adapt and scale to support evolving Co-Brand partnership needs.
- Build and test AI agents. Iterate designs to enhance functionality and user experience. Conduct rigorous testing for reliability and mentor junior team members on best practices.
- Use tools like Databricks, Python, Tableau and Alteryx to create data pipelines and dashboards. Support AI-driven insights and business recommendations for Co-Brand strategic initiatives.
- Monitor AI model performance. Identify areas for enhancement. Implement updates to maintain quality and relevance. Drive continuous improvement of analytical methodologies.
- Lead workstreams on agile teams to support data-driven decision-making, customer segmentation, and strategic partner relationship management.
Required Qualifications, Capabilities, and Skills
- Degree in a scientific field (Computer Science, Engineering, Data Science, Statistics, Mathematics, etc.) with 6+ years of experience in AI/ML or Data Science.
- Experience working in Card, Co-Brand, or other Financial Services verticals.
- Strong understanding of AI models, including large language model (LLM) capabilities and limitations, and experience applying them to business problems.
- Proven experience with statistical analysis, data-driven decision-making, customer segmentation, and pattern identification.
- Strong creative problem-solving skills with the ability to translate complex analytical findings into actionable business recommendations.
- Proficiency in Python and SQL with demonstrated ability to build production-quality analytical solutions.
- Experience with cloud platforms such as AWS, GCP, or Azure, and SDLC concepts.
- Strong communication and collaboration skills, with the ability to present findings to senior stakeholders and work effectively across teams.
- Experience building and contributing to agentic AI architectures and automation frameworks.
Preferred Qualifications, Capabilities, and Skills
- Experience in customer segmentation, strategic analytics, or related fields within financial services.
- Hands-on experience with AWS, Databricks for data management, large-scale data processing, and advanced analytics.
- Understanding of quality assurance practices, model validation, and the importance of data integrity in production environments.
Deep knowledge of machine learning/data science theory, techniques, and tools with experience deploying models at scale.