Ontology Engineer

🕒 il y a 7 jours

🇺🇸 États-Unis – Télétravail

💵 $90 000 - $115 000 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

👷🏻‍♀️ Ingénieur

🦅 Parrain de Visa H1B

info

🗣️🇺🇸🇬🇧 Anglais requis

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Logo of HMH

HMH

1001 - 5000 employés

📚 Éducation

🛍️ eCommerce

Education • eCommerce • Professional Development

HMH est une entreprise éducative spécialisée dans la fourniture de solutions complètes de programmes et d'évaluations couvrant un large éventail de matières. Elle propose des programmes et des ressources pour la littératie, les mathématiques, les sciences, les études sociales et l'apprentissage socio-émotionnel pour les élèves de K-12. De plus, HMH se concentre sur le développement professionnel des éducateurs pour améliorer les stratégies pédagogiques et les résultats des élèves.

Description

• Develops and maintains logical, semantically rich, and extensible ontologies that define and structure knowledge and underpin the K-12 education domain and HMH products. • Supports integration between the ontology management system and source data management repositories, including triple store development and investigation by writing SPARQL queries. • Ensures the accuracy and consistency of ontological structures by performing regular quality checks and updates as needed. • Collaborates with cross-functional teams to understand their information needs and provide ontological solutions. • Creates comprehensive documentation for ontologies and knowledge graphs.

🎯 Exigences

• Advanced degree in philosophy, computer science, information science, or quantitative field, or equivalent experience. • Proficiency in ontology modeling languages such as RDF, OWL, or SHACL and vocabularies such as SKOS. • Familiarity with query languages like SQL and SPARQL or other property graph query languages like Gremlin, openCypher. • Experience with semantic data integration and using graph databases/triplestores. • Skilled in integrating multiple disparate data sets into a common vocabulary and writing effective queries for production environments. • Hands-on experience with high-level programming and scripting languages, such as Python, R, and Java. • Strong software engineering practices applied to semantic and analytics assets: git, pull requests/code review, test/validation practices.

🏖️ Avantages

• Health insurance • Professional development opportunities

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