Senior Data Product Owner — Analytics & Data Strategy

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 110,000 - 160,000; Full time

Job summary

JPMorgan Chase & Co. in Columbus seeks a Data Product Owner to guide analytics products, ensuring data is well documented, high quality, and protected. You will work on customer applications and account opening data, moving from legacy to modernized data and enabling AI/ML use cases.

You will partner with Tech, Product, Analytics, Risk and Control teams to define data requirements, build data dictionaries, and support data delivery to dashboards and models.

Qualifications

• Bachelor's degree in STEM.
• 3+ years in Data Science / related fields.
• Ability to model data with firmwide tooling for high-performance querying.
• Experience with analytics, BI, ML, data warehousing and data modeling.
• Strong knowledge of SQL, databases, Kafka, AWS, and Snowflake.
• Familiarity with NLP/ML toolkits.
• Familiarity with data taxonomy and metadata management.
• Ability to balance short- and long-term goals.

Responsibilities

• Document data requirements and coordinate data creation.
• Model data with long-term vision for querying and LLM use.
• Propose data products from analytics needs and prototypes.
• Support PoCs for natural language querying and roll out to users.
• Help build backlog and user stories for data engineering squads.
• Partner with Technology, Product, Analytics, Operations, Risk, and Control teams to investigate data issues and remediation.
• Maintain documentation of data models, data structures, business rules, metadata, and data delivery processes.

Skills

Data modeling

SQL

Kafka

AWS

Snowflake

NLP/ML tooling

Data governance

Open data standards

Communication

Education

Bachelor's degree in STEM

Tools

Snowflake

AWS

ETL tooling

Job description

JPMorgan Chase & Co. in Columbus seeks a Data Product Owner to guide analytics products, ensuring data is well documented, high quality, and protected. You will work on customer applications and account opening data, moving from legacy to modernized data and enabling AI/ML use cases.

You will partner with Tech, Product, Analytics, Risk and Control teams to define data requirements, build data dictionaries, and support data delivery to dashboards and models.