Data Scientist Lead

This is a unique opportunity to have meaningful impact on a large scale at a leading financial services firm!! You'll need to be a strategic, analytical thinker with enough networking skills to become a trusted advisor and thought leader in the marketing space. Along with leveraging your proficiency with modern data science and analytics tools (including the AI suites that can boost your productivity), you'll clearly and concisely articulate data needs, analytical findings, and process improvements in a way that senior leadership finds persuasive. Job responsibilities Joining our team means you sit in the engine that powers Chase with insights, inspires customer-centric innovation, and answers critical questions around our marketing. Working here means joining a collaborative, supportive team. We want your diverse perspective to help us innovate the next wave of analytical products and solutions for our business. You'll be working with marketing analytics teams across the organization to ensure that the entire firm can effectively and efficiently measure our marketing.

This will involve:

Taking a leading role with peer analytics teams to understand and influence how marketing measures results (datasets, process, and methods) Designing and prototyping key datasets that enable better measurement, including creating the business case and ensuring data quality. Developing and promoting a deep understanding of how AI can streamline and enrich our measurement. Working closely with peers to ensure the quality of your own work as well as the team's. Required qualifications, capabilities and skills Undergraduate or advanced degree in analytical field (e.g., Computer Science, Economics, Mathematics, Statistics, Engineering, Operations Research, Physics), data bootcamp certification, or industry experience in analytical roles (e.g., consulting, modeling, data analysis). Experience with modern data science tools (ex: SQL, AWS, Python), current AI tools (ex: Copilot, Claude), and familiarity with quantitative techniques (ex: regression analysis) - with an appetite for updating this list as new technologies and techniques arrive. Expertise in the scientific method, able to frame a non-technical question as a testable hypothesis and articulate what can or cannot be statistically proven with current or potential data. Able to address business challenges with practical and consultative solutions. Attention to detail, able to spot and correct potential flaws in a dataset or analysis. Strong work management skills, able to keep several projects on track simultaneously and persuasively communicate value of work to senior leaders. Preferred qualifications, capabilities and skills Financial services background. Experience at a top tier analytics consulting firm is a benefit. MBA or other master's degree in a quantitative field.