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.
Requirements
1+ years of experience in Information Technology, data analytics, or related industries
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 is desired.
Experience with graph platforms (e.g., Neo4j, Amazon Neptune), including model design and querying preferred.
Demonstrated ability to conceptualize, design, and refine ontologies to accurately model domain knowledge, entities, relationships, and rules for organizational data preferred.
Experience defining and managing taxonomies, classes, properties, constraints, and semantic relationships using standards such as RDF, OWL, and SKOS a plus.
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.
Solid 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
Medical, pharmacy, dental and vision care.
Wellbeing support such as the BMS Living Life Better program and employee assistance programs (EAP).
Financial well-being resources and a 401(K).
Financial protection benefits such as short- and long-term disability, life insurance, supplemental health insurance, business travel protection and survivor support.
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.
Parental, caregiver, bereavement, and military leave.
Family care services such as adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, and child, elder and pet care resources.
Other perks like tuition reimbursement and a recognition program.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
information modelingdata analyticssemantic model developmentdata ontologiesgraph databasesSDLCDevOpsAgilePythonSQL
Soft skills
communication skillscustomer-oriented mindsetproblem-solvingstakeholder engagementconceptualizationdesign refinementcollaborationadaptabilityproject guidancecontinuous improvement
