Scientist II, Biomarker Sciences/Translation Sciences

Scorpion Therapeutics; California (MO); On-site; USD 120,000 - 180,000; Full time

Job summary

Scorpion Therapeutics is seeking a Scientist II in Biomarker Sciences/Translational Sciences to lead computational analyses of preclinical and clinical datasets, identifying biomarkers, mechanisms of response and pharmacodynamics in oncology.

You will analyze multi-omics data, develop scalable workflows, collaborate across Translational Research, Biomarker, Bioinformatics and Data Science teams, and translate findings into actionable hypotheses and biomarker assays.

Qualifications

• PhD in Cancer Biology, Molecular Oncology, or related field.
• 3+ years postdoctoral or industry experience.
• Expertise in analyzing complex omics datasets and cancer genomics.
• Proficiency in R and Python, statistics, and bioinformatics tools.
• Experience with machine learning and AI approaches.

Responsibilities

• Analyze multi-omics data including bulk and single-cell sequencing.
• Develop scalable workflows.
• Collaborate across Translational Research, Biomarker, Bioinformatics, and Data Science teams.
• Translate findings into actionable hypotheses and biomarker assays.

Skills

R

Python

Statistics

Bioinformatics

ML/AI

Omics analysis

Collaboration

Education

PhD in Cancer Biology

Tools

R

Python

Bioinformatics tools

Cloud-based analytics

Job description

Role

Scientist II, Biomarker Sciences/Translational Sciences, supporting computational analysis of preclinical and clinical datasets to identify biomarkers, mechanisms of response/resistance, and pharmacodynamics in oncology.

Responsibilities

• analyze multi-omics data including bulk and single-cell sequencing
• develop scalable workflows
• collaborate across Translational Research, Biomarker, Bioinformatics, and Data Science teams
• translate findings into actionable hypotheses and biomarker assays

Requirements

• PhD in Cancer Biology, Molecular Oncology, or related field
• 3+ years postdoctoral/industry experience
• expertise in analyzing complex omics datasets, cancer genomics, and translational biology
• proficiency in R/Python, statistical analysis, and bioinformatics tools
• experience with machine learning and AI approaches.

Preferred

• background in oncology drug discovery/development
• experience with longitudinal datasets
• integration of multi-modal data
• cloud-based analytics environments
• knowledge of RAS-driven cancers is a plus.

HighValue: oncology, biomarker discovery, translational research, omics analysis, AI/ML applications, broad cross-functional collaboration, and data integration for biomarker development.

WorkSetup: not specified but implies a research setting.