Principal Data Scientist - AI-Driven Drug Discovery Data

Scorpion Therapeutics; Spring House (PA); On-site; USD 117,000 - 201,000; Full time

Benefits offered by this job

Vacation 120 hrs/yr

Parental leave 480 hrs

Job summary

Scorpion Therapeutics in Spring House, PA, seeks a leader to shape scientific data products for AI-enabled drug discovery and development. You will design interoperable data assets connecting discovery, preclinical, clinical, safety, and real-world evidence, and build AI-ready data services, knowledge graphs, and feature stores.

Collaborate across teams to standardize metadata, governance, and FAIR data principles.

Qualifications

• Master’s or PhD in CS, data engineering, bioinformatics, biomedical informatics, or related fields.
• 5+ years in scientific data engineering, architecture, products, or life sciences informatics.
• Experience delivering enterprise-scale scientific data products for drug discovery or pharmacovigilance.

Responsibilities

• Define and execute a scientific data product strategy across discovery to real-world evidence.
• Design data integration frameworks and harmonization standards (SEND/SDTM/ADaM).
• Lead AWS deployment strategy and scalable data pipelines.
• Develop curated datasets, semantic-ready products, and feature stores.
• Establish metadata quality, lineage, and FAIR principles; monitor data quality.
• Build predictive AI/ML models to support translational safety decisions.

Skills

Data engineering

Data architecture

Life sciences informatics

Drug discovery

Education

Master's or PhD in CS/Data Eng/Bioinformatics

Tools

AWS

Data lakes/lakehouses

SDTM/ADaM/MedDRA

Job description

Scorpion Therapeutics in Spring House, PA, seeks a leader to shape scientific data products for AI-enabled drug discovery and development. You will design interoperable data assets connecting discovery, preclinical, clinical, safety, and real-world evidence, and build AI-ready data services, knowledge graphs, and feature stores.

Collaborate across teams to standardize metadata, governance, and FAIR data principles.