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.