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Strong employer brand plus metro location and mid-level role increase competition despite niche graph specialization.
Knowledge-graph and pharma regulatory expectations make skills moderately transferable across industries.
Explicit 4–7 year requirement plus mandatory knowledge-graph, Databricks, and compliance skills enforce strict filtering.
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Design and deploy connected data solutions combining information modeling, knowledge graphs, and Generative AI to solve complex regulated business problems.
Translate business requirements into scalable AI-driven data products across pharmaceutical and operational domains using technologies like SQL, SPARQL, Databricks, and AWS.
Establish best practices for connected data, ensure compliance with Responsible AI and regulatory frameworks, and promote continuous improvement in data product delivery and adoption.
Master's degree OR Bachelor's degree with 4 to 7 years of experience in Data Science, AI, Computer Science, Information Science, or related field.
Strong practical experience in information modeling, knowledge graph development, and Generative AI applications.
Proficiency in SQL and experience with Databricks or equivalent data/AI platforms.
Knowledge of FAIR data principles and experience with knowledge graph platforms such as Stardog or GraphDB.
Technically strong and strategic data practitioner capable of moving from concept through to scalable implementation in a complex, regulated pharmaceutical environment.
Experienced in collaborating with cross-functional teams to align AI data solutions with business and compliance requirements.
Able to drive innovation and continuous improvement in data-centric and AI-enabled enterprise transformation initiatives.