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Job details:
Role - Data Scientist
Key Skills required - Ontology Engineering, Knowledge Graphs, GCP, semantic data modeling.
Experience - 5-12 yrs
Location - Chennai/Hyderabad
Mode of work - Hybrid
Role Summary:
Data Scientist with deep expertise in ontology engineering and semantic data modeling, with hands-on experience in GCP-native knowledge graph technologies and strong domain exposure in the US Healthcare (Payer or Provider) industry.
The ideal candidate holds a Master’s degree in Data Science (or related field) and has demonstrated experience in designing and implementing scalable knowledge graph solutions to drive data interoperability, analytics, and business insights in healthcare ecosystems.
Key Responsibilities
Ontology & Knowledge Modeling
- Design, develop, and maintain ontologies, taxonomies, and semantic data models aligned with healthcare standards and business domains.
- Build and manage knowledge graphs using RDF, OWL, and related technologies.
- Define and enforce data standards, vocabularies, and schemas to ensure semantic consistency and interoperability.
- Collaborate with healthcare SMEs to translate payer/provider workflows and concepts into formal ontological representations.
GCP Knowledge Graph & Engineering
- Develop and deploy knowledge graph solutions using GCP-native services (e.g., BigQuery, Dataflow, Dataproc, Vertex AI, and graph-based integrations).
- Integrate semantic models with cloud-native data pipelines and enterprise data platforms.
- Work with graph databases and triple stores (e.g., Neo4j, Stardog, or GCP-compatible solutions).
- Implement SPARQL queries, reasoning mechanisms, and scalable data processing pipelines.
Data Science & Analytics
- Apply statistical modeling, machine learning, and graph analytics techniques to derive insights from healthcare data.
- Develop graph-based features, embeddings, and predictive models.
- Perform data exploration, quality assessment, and feature engineering leveraging structured and linked datasets.
Healthcare Domain Application
- Work with data from US Healthcare payer/provider systems such as claims, EHR/EMR, provider networks, and care management.
- Align ontology models with healthcare standards (e.g., FHIR, ICD, CPT, SNOMED).
- Support use cases such as care coordination, population health, fraud detection, and utilization management.
Collaboration & Strategy
- Partner with engineering, product, and business stakeholders to align ontology and knowledge graph strategy with enterprise goals.
- Drive adoption of semantic technologies and knowledge graphs across the organization.
- Mentor junior team members and contribute to best practices in ontology design and governance.
Required Qualifications
- Master’s degree in Data Science, Computer Science, Artificial Intelligence, or a related field.
- 5+ years of experience in data science, with 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: OWL, RDF, RDFS
- Query language: SPARQL
- Knowledge graph frameworks and tools
- Experience working in US Healthcare (Payer or Provider) environments.
- Strong programming skills in Python.
- Experience with graph databases and semantic repositories.
- Solid understanding of:
- Data modeling and data architecture
- Machine learning and statistical analysis
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