Data Scientist Senior Associate

As a Data Scientist Sr. Associate within the Consumer Bank Marketing Analytics team, you will help manage and advance the data infrastructure that powers analytical work across CB Marketing. The data products you support enable analysis behind marketing efforts that acquire millions of accounts each year, giving you the opportunity to make a meaningful impact at scale. You will help maintain and evolve our primary marketing analytics data product, ensuring that trusted, useful, and well-documented data assets are available to analysts and decision-makers.

You will coordinate a roadmap to automate, enhance, and modernize this ecosystem; identify new upstream data sources; increase adoption of existing assets; uncover important gaps; and stay current on emerging AI capabilities that could improve data science and analytics workflows.

Job responsibilities

• Help manage the roadmap and ongoing development of the primary data product used by Consumer Bank Marketing Analytics
• Support the broader CB Marketing data infrastructure, balancing day-to-day reliability with longer-term automation, enhancement, and modernization priorities
• Build, maintain, document, and monitor reusable team data assets with strong controls for data quality, lineage, consistency, and reliability
• Identify and evaluate new upstream data sources, partner with source-system owners, and translate emerging marketing and analytical needs into scalable data solutions
• Develop new ways to deliver useful, accessible data to analysts and business partners, improving speed to insight and reducing duplicative work
• Maintain a clear inventory of available data assets, educate the team on their purpose and appropriate use, drive adoption, and identify gaps that limit analytical capabilities
• Apply knowledge of marketing attribution and the customer journey to ensure data assets support accurate measurement of channel, campaign, and initiative performance
• Create visualizations and narratives that explain the health, coverage, usage, and business value of the data ecosystem to technical and non-technical stakeholders
• Stay current on emerging AI capabilities that could affect data science and analytics, identify relevant use cases, and help incorporate practical opportunities into the team’s innovation roadmap
• Required qualifications, capabilities and skills
• Bachelor’s degree in a quantitative discipline (e.g., Data Science/Analytics, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or related field)
• 3+ years of experience building, maintaining, or managing shared data assets, analytical data products, or data infrastructure used by multiple analysts or business teams
• 3+ years of experience using SQL and at least one of Python or R
• Demonstrated experience using AI-assisted development tools (e.g., GitHub Copilot, Claude Code, or similar) to accelerate analysis and code development
• Working knowledge of marketing attribution concepts, including how customer interactions, channels, campaigns, and conversion outcomes are connected in data
• Experience organizing or contributing to a roadmap or backlog for data products, automation, platform enhancements, or modernization initiatives
• Strong organizational and project management skills, with the ability to prioritize competing needs, manage dependencies, and drive work from concept through implementation and adoption
• Experience partnering with upstream data providers and downstream users to gather requirements, resolve data issues, and deliver scalable solutions
• Strong understanding of data quality, documentation, lineage, controls, and the practices required to maintain trusted team data assets
• Experience using data visualization and storytelling techniques to explain complex data concepts, communicate value, and influence technical and business stakeholders
• Strong written and verbal communication skills, including the ability to educate users, facilitate cross-functional decisions, and translate business needs into data requirements

Preferred qualifications, capabilities and skills

• Master’s degree in a quantitative discipline (e.g., Data Science/Analytics, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or related field)
• Exposure to consumer banking, marketing analytics, marketing measurement, or customer-level data
• Familiarity with cloud data platforms, reusable data models, metadata management, or data catalog tools
• Experience with Tableau or a comparable business intelligence and visualization platform