Senior Data Scientist – Surfaceome Biology

Lead projects to identify, evaluate, and integrate high-value external biomedical datasets for computational biology applications.

Design and implement data pipelines and AI/ML methods to harmonize and analyze diverse biological data to generate insights for target discovery and biomarker development.

Collaborate with global teams to translate integrated data into actionable biological and therapeutic decisions using reproducible data and model products with DataOps and MLOps practices.

PhD in computational biology, bioinformatics, computer science, data science, or related quantitative field preferred; alternatively Master’s or Bachelor’s with 8-12 years related experience.

Strong programming skills in Python, R, or similar languages with experience in reproducible analytical workflows.

Experience with multi-omics and multimodal data integration and qualification of external biomedical datasets from various sources.

Work Experience Required: 8-12 years (if Bachelor’s degree holder) or Industry experience preferred with PhD.

Demonstrated ability to develop and apply advanced AI/ML methods (foundation models, representation learning, knowledge-graph approaches) in biological systems.

Proven success in translating computational analyses into biological insights, target validation evidence, or biomarker hypotheses.

Experience with cloud-scale data processing, workflow orchestration, MLOps practices, and working effectively across cross-functional global teams.