Senior Data Scientist, Biologics Discovery & ML

Scorpion Therapeutics; Spring House (PA); On-site; USD 109,000 - 175,000; Full time

Benefits offered by this job

Medical/dental/vision

Life insurance

Retirement plan/401(k)

Paid time off

Job summary

Scorpion Therapeutics in Spring House, PA seeks a Senior Data Scientist (Biologics Discovery) to design featurization, curate datasets from antibody/protein sequence, construct, assay, and biophysical data, and build trusted ML models.

You will collaborate with ISD and DS/AI teams to ensure reproducible training datasets, establish evaluation frameworks, and champion responsible AI across the DMTL cycle.

Qualifications

• Master’s or Ph.D. in CS/ML/Computational Biology or related field.
• 2+ years applying ML to complex biomedical data.
• Proficiency in Python (PyTorch, scikit-learn) and SQL.
• Experience converting heterogeneous data into robust features.
• Knowledge of leakage and distribution shift risks.
• Ability to collaborate in matrixed R&D.

Responsibilities

• Develop featurization and datasets from sequence, construct, assay, and biophysical data.
• Specify features/labels with data engineers; preserve raw representations.
• Curate, document, and version datasets for reproducibility.
• Collaborate on standardized training datasets and ownership boundaries.
• Partner with discovery scientists to frame ML around decision points.
• Work with ontology and MLOps colleagues to align dataset semantics.
• Champion reproducibility, documentation, and responsible AI.

Skills

Applied ML experience

Dataset curation

Python (PyTorch, scikit-learn)

SQL

Collaboration in matrixed R&D

Education

Master’s or Ph.D. in CS/ML/Computational Biology/Bioinformatics/Statistics

Tools

Python (PyTorch, scikit-learn)

SQL

Cloud training/data infrastructure

Job description

Scorpion Therapeutics in Spring House, PA seeks a Senior Data Scientist (Biologics Discovery) to design featurization, curate datasets from antibody/protein sequence, construct, assay, and biophysical data, and build trusted ML models.

You will collaborate with ISD and DS/AI teams to ensure reproducible training datasets, establish evaluation frameworks, and champion responsible AI across the DMTL cycle.