Data Scientist (Ontology Engineering & Knowledge Graphs)
This Data Scientist role at enGen Global focuses on building ontology engineering and knowledge graph solutions within the US healthcare domain. The hire will design semantic models, deploy GCP-native graph pipelines, and leverage statistical modeling for healthcare insights. Candidates must have a Master's degree, 5+ years of experience, and proficiency in RDF, OWL, and Python. The position operates in a hybrid capacity from Chennai or Hyderabad.
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Experience
5-12 years
Function
Research
Work mode
Hybrid, India
Company
Tier 2
What you will work on
This Data Scientist role at enGen Global focuses on building ontology engineering and knowledge graph solutions within the US healthcare domain. The hire will design semantic models, deploy GCP-native graph pipelines, and leverage statistical modeling for healthcare insights. Candidates must have a Master's degree, 5+ years of experience, and proficiency in RDF, OWL, and Python. The position operates in a hybrid capacity from Chennai or Hyderabad.
TAL's take
Niche specialized domain and stack in healthcare industry within a mid-tier firm.
Very clear and specific role definition focused on ontology and knowledge graphs within healthcare.
Must haves
- Master's degree in Data Science or related field
- 5+ years of experience in data science
- Expertise in ontology engineering and knowledge graphs
- Hands-on experience with GCP-native technologies
- Experience in US Healthcare payer or provider environments
- Strong programming skills in Python
Tools and skills
Nice to have: neo4j, stardog, fhir, icd, cpt, snomed.
About the company
unfamiliar company, default mid-tier.
Posts mentioning enGen Global
Anyone got any insights on Enzen global solutions in Bangalore
I used to work at that company, left because the salary was delayed every month and then they just stopped paying it
Not project, need depth concept
Building projects is fun like any project - web application, android application, or like integrating a ml model, etc. But nowadays, i believe it is not a distinguish factor to stand in tech. One can easily prompt to ai and build it. Instead, we should focus on more in-depth concepts, let say in the web, know how v8 engin internally works, or in db how data is being stored and what the algorithms are being used. In ml learn about maths or algo. How kernal works, how can someone build own redis or how lru cache works etc etc. Basically in the field of softwere engineering more focus should go on internal things. Not like knowing a framework or tech tools. What's your opinion?
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