Principal Scientist, Data Science (Data Products, Integration & Analysis)

Scorpion Therapeutics; Horsham (PA); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Vacation time

Sick leave

Parental leave

Job summary

Scorpion Therapeutics is seeking a senior data product leader to design and evolve AI-ready data products for drug discovery and development. You will connect discovery, preclinical, clinical, safety, and real-world evidence through scalable data architectures and semantic reasoning.

Collaborating with scientists, knowledge architects, AI engineers, and platform teams, you will drive governance, provenance, and FAIR data practices while delivering predictive models to support translational

Qualifications

• Master’s or PhD in CS/Data Engineering/Bioinformatics/Computational Biology or related field.
• 5+ years in scientific data engineering/architecture/products or life sciences informatics.
• Enterprise-scale scientific data product delivery experience.
• Experience supporting drug discovery/development/clinical research/pharmacovigilance.
• Experience developing predictive models in these areas.

Responsibilities

• Define and execute data product strategy across discovery to real-world evidence.
• Design integration frameworks (SEND/SDTM/ADaM/MedDRA/Imaging/Omics).
• Lead AWS deployment strategy; ensure security/governance/AI-readiness.
• Develop curated datasets, feature stores, semantic-ready data products, and AI-ready assets.
• Define metadata standards; implement lineage/provenance/traceability and FAIR; monitor quality.
• Build predictive AIML models for translational safety decision making.

Skills

Advanced analytics

Critical thinking

Data quality/analysis/visualization

Data governance & metadata

Data architecture/modeling/product

Cloud-native platforms

Predictive model development

Education

Master’s or PhD in CS/Data Engineering/Bioinformatics/Computational Biology

Job description

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.
• Work with scientific stakeholders, knowledge architects, AI engineers, and platform teams to deliver high-quality products supporting translational science and patient safety.

Key Responsibilities

• Define and execute scientific data product strategy (discovery, translational science, preclinical safety, clinical development, pharmacovigilance, real-world evidence).
• Design data integration/harmonization frameworks (SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, real-world data).
• Lead AWS deployment strategy; partner on pipelines/data products; ensure security/governance/AI-readiness alignment.
• Develop curated datasets, semantic-ready data products, feature stores, metadata products, scientific data services, and AI-ready assets.
• Define metadata standards; implement lineage/provenance/traceability and FAIR; monitoring and quality controls.
• Build predictive AIML models for translational safety decision making.

Required Qualifications

• Master’s or PhD in CS/Data Engineering/Bioinformatics/Biomedical Informatics/Information Systems/Computational Biology/related.
• 5+ years in scientific data engineering/architecture/products or life sciences informatics.
• Enterprise-scale scientific data product delivery experience.
• Experience supporting drug discovery/development/clinical research/pharmacovigilance.
• Experience developing predictive models in these areas.

Preferred Qualifications

• Knowledge graphs/semantic architectures/GraphRAG; AI-ready products/feature stores; ontology-driven integration; cloud/platform partnerships; highly regulated scientific environments.

Skills (Required/Preferred listed)

• Advanced analytics
• critical thinking
• data quality/analysis/reporting/visualization
• data governance & metadata
• data architecture/modeling/product design
• cloud-native platforms
• predictive model development.

Benefits (time off)

• Vacation 120h/yr
• Sick time 40h/yr (48h CO; 56h WA)
• Holiday pay 13 days/yr
• Parental leave 480h (within one year)
• other stated leave options included.