Senior Data Scientist, Biologics Discovery

Scorpion Therapeutics; New Jersey; On-site; USD 109,000 - 175,000; Full time

Benefits offered by this job

Annual bonus eligibility

Medical/dental/vision/life insurance

401(k) plan

Job summary

Scorpion Therapeutics seeks a Senior Data Scientist to design featurization and curate datasets for antibody/protein sequences, constructs, assays and biophysical data. You will build and evaluate ML models, ensuring trustworthiness and reproducibility, while collaborating with ISD to strengthen molecular property models.

The role emphasizes standardized, traceable training datasets, robust feature definitions, and responsible AI within a matrixed R&D environment.

Qualifications

• M.S. or Ph.D. in CS/ML/Computational Biology/Bioinformatics/Statistics or related field.
• 2+ years applied ML (model development/evaluation/dataset curation) on complex scientific/biomedical data.
• Proficiency in Python (PyTorch, scikit-learn) and SQL.
• Experience converting heterogeneous experimental data into robust features/training sets; exposure to cloud training/data infrastructure.
• Understanding of evaluation/validation, leakage, and distribution shift.
• Ability to collaborate in a matrixed R&D environment.

Responsibilities

• Design featurization and dataset curation for antibody/protein sequence, constructs, assay, and biophysical data.
• Build and evaluate applied ML models; define evaluation frameworks to keep models trustworthy.
• Collaborate with data-infrastructure partners and In Silico Discovery (ISD) to strengthen ISD’s molecular property models.
• Develop featurization and model-ready datasets.
• Specify features/labels/aggregation levels with data engineers; preserve raw representations.
• Curate, document, and version datasets for reproducibility and traceability.
• Partner with ISD on standardized, traceable training datasets; align on DS vs. ISD ownership.
• Frame ML problems around decision points in the DMTL cycle.
• Work with ontology and MLOps teams to ensure consistent semantics and reliable model deployment.
• Champion reproducibility, documentation, and responsible AI.

Skills

Python

PyTorch

scikit-learn

SQL

Applied ML

Data curation

Education

M.S./Ph.D. in CS/ML/Bioinformatics/Statistics

Tools

Cloud platforms

SQL tooling

Job description

Senior Data Scientist (Biologics Discovery)

Position Summary

• Design featurization and dataset curation for antibody/protein sequence, constructs, assay, and biophysical data.
• Build and evaluate applied ML models; define evaluation frameworks to keep models trustworthy.
• Collaborate with data-infrastructure partners and In Silico Discovery (ISD) to strengthen ISD’s molecular property models.

Key Responsibilities

• Develop featurization and model-ready datasets.
• Specify features/labels/aggregation levels with data engineers; preserve raw representations.
• Curate, document, and version datasets for reproducibility and traceability.
• Partner with ISD on standardized, traceable training datasets; align on DS vs. ISD ownership.
• Frame ML problems around decision points in the DMTL cycle.
• Work with ontology and MLOps teams to ensure consistent semantics and reliable model deployment.
• Champion reproducibility, documentation, and responsible AI.

Qualifications

Required

• M.S. or Ph.D. in CS/ML/Computational Biology/Bioinformatics/Statistics or related field.
• 2+ years applied ML (model development/evaluation/dataset curation) on complex scientific/biomedical data.
• Proficiency in Python (PyTorch, scikit-learn) and SQL.
• Experience converting heterogeneous experimental data into robust features/training sets; exposure to cloud training/data infrastructure.
• Understanding of evaluation/validation, leakage, and distribution shift.
• Ability to collaborate in a matrixed R&D environment.

Preferred

• Biologics, antibody/protein sequence models, or protein language models.
• Active learning, Bayesian optimization, or sequence-based generative models.
• Familiarity with assay/biophysical data and developability endpoints.
• MLOps, experiment tracking, model monitoring.
• Ontologies/knowledge graphs for AI-ready datasets.

Benefits/Compensation (as stated)

• Base pay range: $109,000–$174,800; annual performance bonus eligibility; medical/dental/vision/life and disability/other listed insurance.
• Pension and 401(k) eligibility.
• Vacation up to 120 hours/year; sick time up to 40 hours/year; holiday/floating holidays up to 13 days/work-personal-family time up to 40 hours/year.

Locations

• Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ, USA; or Madrid, Spain. No remote option.