Location: Bengaluru, Karnataka, India

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.

Join JPMorgan Chase's Cards Data & Analytics team, using data science and business insights to drive impactful outcomes.