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Data Scientist Senior Associate

JPMorgan Chase
Columbus, USA
Full-time
Senior · 3+ years experience
Onsite
Discovered 2 weeks ago
pythonsqltableau

Full Job Posting

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
  • 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
  • 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

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
  • 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

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

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