Proteomics Data Scientist

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BIOWEG is seeking a creative, driven, and scientifically adventurous Proteomics Data Scientist to join a fast-paced, high-energy team developing next-generation peptide-based technologies for advanced materials and sustainable separation applications. This project forms part of the research project in collaboration with TU Berlin to design to accelerate breakthrough Proteomics application technology. You will be joining an environment that moves with startup energy, rapid decision-making, a strong emphasis on innovation and cutting edge science.

BIOWEG mission contributes directly to global sustainability enabling new approaches for circular economy. The work supports circular‑economy principles and advances long‑term technological resilience at both European and global levels.

In this role, you will contribute to the interpretation of complex proteomics datasets, the development of advanced analysis pipelines, and the optimisation of computational workflows. Your ideas, creativity, and problem‑solving abilities will play an important part in shaping experimental strategy and supporting rapid scientific progress within a time‑sensitive research framework.

Key Responsibilities

• Mass Spectrometry Data Analysis : Interpret, quantify, and statistically evaluate high‑resolution LC‑MS/MS peptide datasets, streamlining DDA/DIA workflows and generating insights that guide experimental decision‑making.
• Software and Workflow Development : Design and optimise computational pipelines with a focus on innovation, robustness, sensitivity, and speed. Implement workflow improvements that accelerate processing, reduce bottlenecks, and expand discovery potential.
• Computational Infrastructure & Data Management : Manage computational resources, servers, data storage, and workflow automation. Ensure reproducible, well‑documented, and scalable analytical pipelines suited to rapid project development.
• Advanced Proteomics Approaches : Apply and develop analytical strategies to evaluate peptide behaviour, interaction patterns, and modification landscapes. Optionally analyse datasets using crosslinking MS search tools and integrate orthogonal data streams into clear, actionable summaries.
• Data Integration and Collaboration : Work closely with peptide chemists, mass spectrometrists, and materials scientists to interpret results and inform experimental planning. Collaborate with TU Berlin to maintain analytical alignment, data quality and reproducibility.
• Quality Control and Troubleshooting : Perform rigorous QC on raw and processed datasets to ensure analytical reliability. Troubleshoot computational and workflow challenges with a proactive, inventive mindset and adapt rapidly to time‑critical project demands.

Qualifications

• Strong experience analysing peptide‑based LC‑MS/MS datasets from Orbitrap mass spectrometers.
• Proficiency with major proteomics software platforms (e.g. MaxQuant, MSFragger, DIA‑NN, Proteome Discoverer).
• Understanding of peptide identification algorithms, quantification strategies, and FDR control.
• Ability to work collaboratively across computational and experimental teams.

Highly Desirable

• Experience analysing datasets acquired on Orbitrap Astral analyzers.
• Experience with R or Python for statistical analysis and workflow development.
• Experience handling large datasets, LFQ/DIA quantification, PTM analysis, or chromatographic profiling.
• Familiarity with crosslinking MS or other specialised proteomics workflows.
• Knowledge of data visualisation and reporting tools.
• Strong background in chemistry or chemical biology, enabling confident interpretation of peptide mass shifts, and complex modification patterns.
• Ability to interpret unexpected peptide modifications, including mass shifts arising from interactions with chemical reagents or metal‑containing environments.
• Experience developing or applying machine learning or statistical models to analyse proteomics datasets or predict peptide properties.
• Experience developing, maintaining, or contributing to proteomics data analysis software or computational tools in an academic or research environment.
• Experience managing servers, HPC environments, or computational infrastructure for server‑based computing.
• Experience in applied, translational, or industry‑oriented R&D environments.

This position is based in Berlin, within a collaborative framework involving BIOWEG GmbH and Technische Universitat Berlin. You will be joining a multidisciplinary, intellectually engaged team spanning peptide chemistry, analytical science, mass spectrometry, materials development, and computational analysis. The project environment combines academic rigour with a startup‑style agility, creativity, and momentum, offering substantial scope to contribute meaningfully to scientific direction and technological outcomes.

Seniority level: Mid‑Senior level | Employment type: Full‑time | Job function: Engineering and Information Technology

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