Manager, Ontology - Data Product Health & Operations

Manager, Ontology - Data Product Health & Operations

The Manager, Ontology - Data Product Governance will be an Individual contributor on the Data Product Governance, Strategy, & Operations team, supporting Product Health & Operations initiatives for Data Products. This work will include:

• Defining “Data Product Health” and related metrics (in conversation with other initiatives to define data health, such as ontology health and data asset health)

• Monitoring ongoing execution of controls and standards 

• Defining Data Product reporting cadence and communication strategies (for example defining roles and responsibilities in reporting, aligning on consistent reporting across teams)

• Partnering with DA and Product partners to ensure Data Product stakeholders have access to the data they need for ongoing reporting and remediation/investigations

• Strategic development of Data Product operations, sharing best practices across LoBs

• Working effectively with colleagues to execute our Data Product Health and Operations strategy (such as communicating program strategy and delegating work effectively without direct supervision)

 

Role-Based Competencies

• Ability to define and measure success and health of a product and related operations (for example KRs, KPIs, metric targets), including providing insights and analysis that enable strategic decision making, as well as providing views into the data to enable others to do their own analyses. 

• Ability to turn data insights into operational processes and/or improvements. (in example identifying the right areas to invest to improve a business process or implement a new one).

• Ability to analyze and implement knowledge organization strategies using tools capable of machine learning and semantic enrichment.

• Ability to maintain awareness of competitor and industry developments related to ontology use, linked data, semantic technology, graph databases, knowledge organization, data modeling, and metadata.

• Able to maintain and update data and models according to industry best practice. 

• Able to support knowledge organization workshops in order to further enhance enterprise ontology, taxonomy, or data models.

• Able to assist in the implementation and support of data standardization and ontology governance strategies and processes.

• Able to develop a strong understanding of the Capital One business, processes, customers, users, and business needs to better solve Data Management problems.

• Able to see and communicate the big picture in an inspiring way. Determines opportunity and risks through comprehensive analysis of current and future trends. 

• Has very strong research skills.

• Able to communicate and present ideas clearly and with confidence. Delivers presentations and status updates suited to the characteristics and needs of the audience.

• Able to foster strong relationships with business partners, supporting semantic projects across departments. Develops a supportive and helpful culture for assistance in projects and daily support interactions.

• Continually focused on improving the responsiveness and quality of the solutions delivered.

• Exhibits high energy, passion, self-motivation, and creativity for problem solving.

 

Basic Qualifications 

• Bachelor’s degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics

• At least 4 years’ experience in a metadata field of work (ontology, taxonomy, semantics or computational linguistics)

• At least 4 years’ experience or training in using W3C standards including linked and canonical data and ontologies (JSON, XML, RDF, RDFS, OWL, and SKOS)

• At least 4 years’ experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World)

• At least 4 years’ experience or training with SQL or SPARQL

 

Preferred Qualifications

• Master’s degree or PhD in information science, computer science, engineering, library science, ontology, semantics or computational linguistics

• Understanding o