Senior Biologics Discovery Data Scientist

Scorpion Therapeutics; Raritan (NJ); On-site; USD 109,000 - 175,000; Full time

Job summary

Scorpion Therapeutics in New Jersey seeks a Senior Data Scientist (Biologics Discovery) to build data-facing ML capabilities for our ISD collaboration. You will design featurization, curate datasets from antibody/protein sequence, constructs, assays and biophysical data, and define evaluation frameworks to make models faster and more trustworthy.

You will partner with data engineers and ISD to hand off standardized training data, preserve raw representations, and frame ML problems within the

Qualifications

• Requires: Master's/PhD in CS/ML/Computational Biology/Statistics or related field; 2+ years applied ML on scientific/biomedical data; proficiency in Python and SQL; experience with heterogeneous data features and training sets; understanding of evaluation/validation, leakage, and distribution shift; ability to collaborate in matrixed R&D.

Responsibilities

• Design featurization and curate datasets from antibody/protein sequence, construct, assay, and biophysical data.
• Collaborate with data engineers to define features/labels/aggregation levels; preserve raw representations.
• Curate, document, and version datasets for reproducibility and traceability.
• Partner with ISD to hand off standardized, traceable training datasets; align ownership boundaries.
• Frame ML problems around the DMTL cycle and ensure reliable model movement into use.
• Work with ontology and MLOps teams to ensure consistent semantics and reliable model deployment.
• Champion reproducibility, documentation, and responsible AI.

Skills

Applied ML

Python (PyTorch)

SQL

Data curation

Collaboration

Education

Master's or PhD in CS/ML/Computational Biology

Tools

PyTorch

scikit-learn

SQL

Job description

Scorpion Therapeutics in New Jersey seeks a Senior Data Scientist (Biologics Discovery) to build data-facing ML capabilities for our ISD collaboration. You will design featurization, curate datasets from antibody/protein sequence, constructs, assays and biophysical data, and define evaluation frameworks to make models faster and more trustworthy.

You will partner with data engineers and ISD to hand off standardized training data, preserve raw representations, and frame ML problems within the