Computational Biologist

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Computational Biologist \| Oncology \& Multi‑omics

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Location:

Berlin, Germany, open to Hybrid, Europe

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Engagement:

Full‑time, permanent

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Sector:

Biotech \| Oncology \| AI‑driven Drug Discovery

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Client:

Confidential (Well‑funded, AI‑native oncology biotech)

🗣️ English language skills

The Opportunity

A fast‑growing, AI‑driven biotech is seeking a

Computational Biologist

to operate at the intersection of oncology, multi‑omics and data science, with a genuine company‑level remit.

Founded by leaders from world‑class academic and clinical institutions, the organisation works closely with global pharmaceutical partners to translate complex biological data into real drug discovery and translational decisions.

The Role

You will own multi‑omics data modalities end-to-end and help define how complex biological data is processed, interpreted and validated across the organisation.

Beyond building and harmonising pipelines, you will play a key role in shaping the biological and computational strategy for a multimodal oncology target discovery platform, working closely with ML researchers, discovery scientists, engineers and external pharma collaborators.

Your work will directly influence target identification, biomarker discovery and portfolio decisions in oncology.

This Role Is Well Suited To

• A computational biologist looking for

greater scientific ownership and strategic influence

• An industry scientist who enjoys working across biology, data and ML, without needing to be an ML specialist
• Someone motivated by

translational impact

, not just methodological novelty

• A high‑autonomy operator who thrives in fast‑moving, scientifically rigorous environments

Key Responsibilities

• Own and scale multi‑omics pipelines across bulk and single‑cell transcriptomics, with exposure to spatial, proteomics and epigenomics
• Shape biological and computational strategy for multimodal oncology target and biomarker discovery
• Partner with internal discovery teams and external pharma collaborators on feasibility, study design and interpretation
• Translate machine‑learning outputs into biologically sound, decision‑ready hypotheses
• Set standards for data quality, statistical robustness and scientific best practice

Ideal Profile

Essential

• PhD or MSc in Computational Biology, Bioinformatics or a related field
• Strong background in computational oncology, including target identification and biomarker discovery
• Industry experience in biotech and/or pharma with end‑to‑end ownership of multi‑omics or translational programmes
• Advanced hands‑on skills in Python and R, taking analyses from prototype to production
• Deep experience with bulk and single‑cell transcriptomics
• Clear communicator, comfortable engaging technical and non‑technical stakeholders
• High‑autonomy, low‑ego operator able to drive strategy and execution

Nice to Have

• Familiarity with machine learning concepts and effective collaboration with ML teams
• Experience with multimodal data integration in oncology settings
• Exposure to cloud infrastructure and modern data or ML tooling
• Prior experience working directly with pharmaceutical partners

How to Apply

For a confidential discussion or to express interest, please contact

Valtera Group

directly.