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Principal Scientist, Data Science; Data Products, Integration & Analysis
Job in
Camden, Camden County, New Jersey, 08100, USA
Listed on 2026-08-30
Listing for:
Scorpion Therapeutics
Full Time
position Listed on 2026-08-30
Job specializations:
-
IT/Tech
Data Engineering, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Position Summary
- - Lead design, implementation, and evolution of scientific data products and integration strategies for AI-enabled drug discovery and development.
- - Create scalable, interoperable, AI-ready data products connecting discovery, preclinical, clinical, safety, and real-world evidence.
- - Establish data architecture, integration strategy, metadata framework, and productization approach for semantic reasoning, knowledge graphs/GraphRAG, advanced analytics, and agentic AI.
- - Define and execute scientific data product strategy across discovery research, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
- - Design integration/harmonization frameworks (SEND, SDTM, ADaM, MedDRA, imaging, omics, biomarker, pathology, real-world data).
- - Lead AWS-deployed implementation strategy; ensure alignment with enterprise architecture, security, governance, and AI readiness.
- - Develop curated/semantic-ready datasets, feature stores, metadata products, scientific data services, and AI-ready assets; define onboarding/transformation/validation/publication patterns.
- - Define metadata/data quality standards; implement lineage/provenance/traceability and FAIR principles.
- - Build predictive AIML models to support translational safety decision-making.
- - Partner with scientific and technical stakeholders to translate scientific questions into scalable solutions.
- - Master’s or PhD in CS, Data Engineering, Bioinformatics, Biomedical Informatics, Information Systems, Computational Biology, or related discipline.
- - 5+ years in scientific data engineering/architecture/products or life sciences informatics.
- - Experience designing enterprise-scale scientific data products; supporting drug discovery/development, clinical research, or pharmacovigilance.
- - Experience developing predictive models in those domains.
- - Knowledge graphs/semantic architectures/GraphRAG; AI-ready data products/feature stores; ontology-driven integration.
- - Partnering with cloud providers/external platform teams; regulated scientific environments.
- - Vacation (120 hrs/yr);
Sick time (40 hrs/yr; CO 48; WA 56);
Holiday pay incl. floating (13 days/yr);
Work/Personal/Family Time (up to 40 hrs/yr);
Parental Leave (480 hrs/1 year);
Bereavement Leave (240 hrs immediate family; extended 40 hrs/yr);
Caregiver Leave (80 hrs/52-week period);
Volunteer Leave (32 hrs/yr);
Military Spouse Time-Off (80 hrs/yr).
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