Data Product Owner-Senior Associate

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

Champion innovation at the intersection of technology and business, guiding cross-functional teams to deliver analytics products that drive real value.

As successful Data Product Owner on the Digital Data Owner Team, you play a key role in the firm's agenda of enabling the business to drive faster innovation through the use of its data by ensuring that data is clearly documented, of good quality, and well-protected. You'll be responsible for customer application and account opening, data that is created, published to the data lake, or consumed for advanced analytics or AI/ML use cases. You'll serve as a subject matter expert to help define and classify data critical to their product, support change management from legacy to modernized data, and collaborate with technology and business partners to execute on data requirements. Additionally, you'll help identify, monitor, and mitigate data risks throughout the data life cycle, and simplify the work involved in getting data from generation to conversion into dashboards, models, and natural language queries.

Job responsibilities

• Document data requirements for your product, coordinate with technology to get the data created, and work with business partners to help manage change from legacy data to modernized data.
• Model the data with a long-term vision to enable efficient querying, natural language querying, and use in LLMs; utilize the business data dictionary and business metadata from tech and product teams to describe the data in simple, understandable terms.
• Contribute ideas for data products by understanding analytics needs and pain points; help create prototypes that analytics and data engineering teams can use as requirements in productizing the datasets.
• Support the development of proof of concepts for natural language querying of the data, and collaborate with analytics, data science, and other stakeholders to roll out the capability to business users.
• Support the team in building the backlog, grooming initiatives, and creating user stories to help data engineering scrum teams publish new data and create data products.
• Partner with Technology, Product, Analytics, Operations, Risk, and Control teams to investigate data issues, identify root causes, and support timely remediation.
• Maintain comprehensive documentation of data models, data structures, business rules, metadata, and data delivery processes.

Required qualifications, capabilities, and skills

• Bachelor's degree in an applicable STEM field
• 3+ years of working experience in Data Science, Computer Science, Information Systems, Data Analytics, or a related field.
• Ability to generate data models using firmwide tooling and designs for high-performance querying/reporting
• Experience with data technologies such as analytics, business intelligence, machine learning, data warehousing and data modeling.
• Working knowledge of data management, metadata, data quality, privacy/security, retention, and governance concepts.
• Strong knowledge of SQL, database concepts, Kafka, Amazon Web Services (AWS), and Snowflake
• Familiarity with natural language processing, machine learning, and deep learning toolkits (such as TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
• Familiarity with open data standards, data taxonomy and vocabularies, and metadata management
• Able to balance short-term goals and long-term vision in complex environments.