Data Scientist (Ontology Engineering & Knowledge Graphs)

As a Data Scientist, you will be responsible for utilizing your expertise in ontology engineering and semantic data modeling to drive data interoperability, analytics, and business insights in the US Healthcare industry. Your primary

will include: - Designing, developing, and maintaining ontologies, taxonomies, and semantic data models aligned with healthcare standards and business domains. - Building and managing knowledge graphs using technologies such as RDF, OWL, and related tools. - Defining and enforcing data standards, vocabularies, and schemas to ensure semantic consistency and interoperability. - Collaborating with healthcare SMEs to translate payer/provider workflows and concepts into formal ontological representations. You will also be working on GCP Knowledge Graph & Engineering tasks such as: - Developing and deploying knowledge graph solutions using GCP-native services like BigQuery, Dataflow, Dataproc, Vertex AI, and graph-based integrations. - Integrating semantic models with cloud-native data pipelines and enterprise data platforms. - Implementing SPARQL queries, reasoning mechanisms, and scalable data processing pipelines. Additionally,

will involve Data Science & Analytics

such as: - Applying statistical modeling, machine learning, and graph analytics techniques to derive insights from healthcare data. - Developing graph-based features, embeddings, and predictive models. - Performing data exploration, quality assessment, and feature engineering leveraging structured and linked datasets. In terms of Healthcare Domain Application, you will: - Work with data from US Healthcare payer/provider systems like claims, EHR/EMR, provider networks, and care management. - Align ontology models with healthcare standards such as FHIR, ICD, CPT, SNOMED. - Support use cases like care coordination, population health, fraud detection, and utilization management. Your collaboration and strategy tasks will involve: - Partnering with engineering, product, and business stakeholders to align ontology and knowledge graph strategy with enterprise goals. - Driving adoption of semantic technologies and knowledge graphs across the organization. - Mentoring junior team members and contributing to best practices in ontology design and governance. For this role, you are required to have: - Masters degree in Data Science, Computer Science, Artificial Intelligence, or a related field. - 5+ years of experience in data science with a strong focus on ontology engineering and knowledge graphs. - Hands-on experience with GCP-native technologies and cloud-based data architecture. - Strong expertise in ontology languages, query languages, knowledge graph frameworks, tools, US Healthcare environments, programming skills in Python, graph databases, semantic repositories, data modeling, data architecture, machine learning, and statistical analysis. As a Data Scientist, you will be responsible for utilizing your expertise in ontology engineering and semantic data modeling to drive data interoperability, analytics, and business insights in the US Healthcare industry. Your primary