Senior Manager, GPS Knowledge Systems
Bristol-Myers Squibb
Senior Manager, GPS Knowledge Systems
Job Description
Develop information models leveraging emerging technologies to deliver business value. Design semantic models and data ontologies to support GPS information model and optimal AI deployment. Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment). Evaluate high-ROI technologies for inclusion in the technology roadmap. Partner with stakeholders to capture business needs. Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders. Translate complex concepts for various stakeholders. Guide large, complex projects and collaborate across functions. Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. 5+ years of progressive experience in Information Technology, data analytics, or related industries, with a proven track record of leadership and innovation. 1+ year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments. Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling. Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying. Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data. Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS. Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval is a plus. Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala). Experience with cloud environments and services, preferably AWS. Experience with DevOps principles for CI/CD pipelines. Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc. Experience deploying AI models is highly desirable. Experience with systems using the Model Context Protocol (MCP) to interact with AI models is highly desirable. Hands-on experience with agile methodologies and tools such as JIRA. Experience with ELT and data engineering processes is a plus. Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions is a plus. Experience with API integration for data ingestion and extraction. Proven experience guiding large, complex projects. Strong communication skills to explain the business value of data model projects and operations. A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvement. Ability to work effectively in a matrixed organization and across global locations. A bachelor's degree in a quantitative or scientific discipline is required. Advanced degrees (MS. or Ph.D.) in relevant fields are preferred. Occasional travel to BMS locations throughout the world is anticipated.
Key Responsibilities
- Develop information models leveraging emerging technologies to deliver business value
- Design semantic models and data ontologies to support GPS information model and optimal AI deployment
- Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment)
- Evaluate high-ROI technologies for inclusion in the technology roadmap
- Partner with stakeholders to capture business needs
- Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders
- Translate complex concepts for various stakeholders
- Guide large, complex projects and collaborate across functions
Required Qualifications
- + years of progressive experience in Information Technology, data analytics, or related industries
- + year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases
- Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments
- Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling
- Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying
- Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data
- Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS
- Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala)
- Experience with cloud environments and services, preferably AWS
- Experience with DevOps principles for CI/CD pipelines
- Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc.
- Hands-on experience with agile methodologies and tools such as JIRA
- Proven experience guiding large, complex projects
- A bachelor's degree in a quantitative or scientific discipline
Preferred Qualifications
- Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval
- Experience deploying AI models
- Experience with systems using the Model Context Protocol (MCP) to interact with AI models
- Experience with ELT and data engineering processes
- Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions
- Experience with API integration for data ingestion and extraction
- Advanced degrees (MS. or Ph.D.) in relevant fields
Skills Required
- Strong communication skills to explain the business value of data model projects and operations
- A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvement
- Ability to work effectively in a matrixed organization and across global locations
Benefits & Perks
- Paid national holidays and optional holidays
- Global Shutdown Days between Christmas and New Year's holiday
- Up to 120 hours of paid vacation
- Up to two (2) paid days to volunteer
- Sick time off
- Summer hours flexibility
Additional Requirements
- Occasional travel to BMS locations throughout the world
Locations
- New Brunswick NJ, United States
- Devens MA, United States
Salary
Estimated Salary Rangemedium confidence
150,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Strong communication skills to explain the business value of data model projects and operationsintermediate
- A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvementintermediate
- Ability to work effectively in a matrixed organization and across global locationsintermediate
Required Qualifications
- + years of progressive experience in Information Technology, data analytics, or related industries (experience)
- + year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases (experience)
- Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments (experience)
- Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling (experience)
- Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying (experience)
- Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data (experience)
- Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS (experience)
- Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala) (experience)
- Experience with cloud environments and services, preferably AWS (experience)
- Experience with DevOps principles for CI/CD pipelines (experience)
- Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc. (experience)
- Hands-on experience with agile methodologies and tools such as JIRA (experience)
- Proven experience guiding large, complex projects (experience)
- A bachelor's degree in a quantitative or scientific discipline (experience)
Preferred Qualifications
- Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval (experience)
- Experience deploying AI models (experience)
- Experience with systems using the Model Context Protocol (MCP) to interact with AI models (experience)
- Experience with ELT and data engineering processes (experience)
- Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions (experience)
- Experience with API integration for data ingestion and extraction (experience)
- Advanced degrees (MS. or Ph.D.) in relevant fields (experience)
Responsibilities
- Develop information models leveraging emerging technologies to deliver business value
- Design semantic models and data ontologies to support GPS information model and optimal AI deployment
- Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment)
- Evaluate high-ROI technologies for inclusion in the technology roadmap
- Partner with stakeholders to capture business needs
- Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders
- Translate complex concepts for various stakeholders
- Guide large, complex projects and collaborate across functions
Benefits
- general: Paid national holidays and optional holidays
- general: Global Shutdown Days between Christmas and New Year's holiday
- general: Up to 120 hours of paid vacation
- general: Up to two (2) paid days to volunteer
- general: Sick time off
- general: Summer hours flexibility
Tags & Categories
Answer 10 quick questions to check your fit for Senior Manager, GPS Knowledge Systems @ Bristol-Myers Squibb.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs
Senior Manager, GPS Knowledge Systems
Bristol-Myers Squibb
Senior Manager, GPS Knowledge Systems
Job Description
Develop information models leveraging emerging technologies to deliver business value. Design semantic models and data ontologies to support GPS information model and optimal AI deployment. Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment). Evaluate high-ROI technologies for inclusion in the technology roadmap. Partner with stakeholders to capture business needs. Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders. Translate complex concepts for various stakeholders. Guide large, complex projects and collaborate across functions. Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. 5+ years of progressive experience in Information Technology, data analytics, or related industries, with a proven track record of leadership and innovation. 1+ year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments. Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling. Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying. Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data. Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS. Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval is a plus. Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala). Experience with cloud environments and services, preferably AWS. Experience with DevOps principles for CI/CD pipelines. Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc. Experience deploying AI models is highly desirable. Experience with systems using the Model Context Protocol (MCP) to interact with AI models is highly desirable. Hands-on experience with agile methodologies and tools such as JIRA. Experience with ELT and data engineering processes is a plus. Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions is a plus. Experience with API integration for data ingestion and extraction. Proven experience guiding large, complex projects. Strong communication skills to explain the business value of data model projects and operations. A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvement. Ability to work effectively in a matrixed organization and across global locations. A bachelor's degree in a quantitative or scientific discipline is required. Advanced degrees (MS. or Ph.D.) in relevant fields are preferred. Occasional travel to BMS locations throughout the world is anticipated.
Key Responsibilities
- Develop information models leveraging emerging technologies to deliver business value
- Design semantic models and data ontologies to support GPS information model and optimal AI deployment
- Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment)
- Evaluate high-ROI technologies for inclusion in the technology roadmap
- Partner with stakeholders to capture business needs
- Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders
- Translate complex concepts for various stakeholders
- Guide large, complex projects and collaborate across functions
Required Qualifications
- + years of progressive experience in Information Technology, data analytics, or related industries
- + year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases
- Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments
- Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling
- Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying
- Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data
- Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS
- Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala)
- Experience with cloud environments and services, preferably AWS
- Experience with DevOps principles for CI/CD pipelines
- Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc.
- Hands-on experience with agile methodologies and tools such as JIRA
- Proven experience guiding large, complex projects
- A bachelor's degree in a quantitative or scientific discipline
Preferred Qualifications
- Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval
- Experience deploying AI models
- Experience with systems using the Model Context Protocol (MCP) to interact with AI models
- Experience with ELT and data engineering processes
- Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions
- Experience with API integration for data ingestion and extraction
- Advanced degrees (MS. or Ph.D.) in relevant fields
Skills Required
- Strong communication skills to explain the business value of data model projects and operations
- A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvement
- Ability to work effectively in a matrixed organization and across global locations
Benefits & Perks
- Paid national holidays and optional holidays
- Global Shutdown Days between Christmas and New Year's holiday
- Up to 120 hours of paid vacation
- Up to two (2) paid days to volunteer
- Sick time off
- Summer hours flexibility
Additional Requirements
- Occasional travel to BMS locations throughout the world
Locations
- New Brunswick NJ, United States
- Devens MA, United States
Salary
Estimated Salary Rangemedium confidence
150,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Strong communication skills to explain the business value of data model projects and operationsintermediate
- A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvementintermediate
- Ability to work effectively in a matrixed organization and across global locationsintermediate
Required Qualifications
- + years of progressive experience in Information Technology, data analytics, or related industries (experience)
- + year experience working on information model relevant workflows and/or tools: semantic model development, data ontologies, application of graph databases (experience)
- Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, ideally in regulated environments (experience)
- Experience designing, implementing, and managing graph models and, ideally, applications related to information modeling (experience)
- Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying (experience)
- Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data (experience)
- Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS (experience)
- Significant experience with programming languages relevant to managing data and information models (e.g., Python, Java, Scala) (experience)
- Experience with cloud environments and services, preferably AWS (experience)
- Experience with DevOps principles for CI/CD pipelines (experience)
- Proficiency with modern analytics tools and technologies, potentially including GitHub, SQL, R, dbt, Domino, Tableau, etc. (experience)
- Hands-on experience with agile methodologies and tools such as JIRA (experience)
- Proven experience guiding large, complex projects (experience)
- A bachelor's degree in a quantitative or scientific discipline (experience)
Preferred Qualifications
- Experience with AI systems that utilize Retrieval-Augmented Generation (RAG) and vector databases for effective information retrieval (experience)
- Experience deploying AI models (experience)
- Experience with systems using the Model Context Protocol (MCP) to interact with AI models (experience)
- Experience with ELT and data engineering processes (experience)
- Experience building and operationalizing predictive models, simulation, optimization frameworks, and AI solutions (experience)
- Experience with API integration for data ingestion and extraction (experience)
- Advanced degrees (MS. or Ph.D.) in relevant fields (experience)
Responsibilities
- Develop information models leveraging emerging technologies to deliver business value
- Design semantic models and data ontologies to support GPS information model and optimal AI deployment
- Ensure adherence to SDLC and analytics best practices (scalability, version control, documentation, deployment)
- Evaluate high-ROI technologies for inclusion in the technology roadmap
- Partner with stakeholders to capture business needs
- Gather business requirements, define measurable outcomes, and deliver analytical product plans for diverse stakeholders
- Translate complex concepts for various stakeholders
- Guide large, complex projects and collaborate across functions
Benefits
- general: Paid national holidays and optional holidays
- general: Global Shutdown Days between Christmas and New Year's holiday
- general: Up to 120 hours of paid vacation
- general: Up to two (2) paid days to volunteer
- general: Sick time off
- general: Summer hours flexibility
Tags & Categories
Answer 10 quick questions to check your fit for Senior Manager, GPS Knowledge Systems @ Bristol-Myers Squibb.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs