data scientist

Required Experience & Skills

• Education: PhD, MSc, or BSc in Bioinformatics, Computational Biology, Data Science, Proteomics, Systems Biology, or a related quantitative field.
• Domain Expertise: Strong understanding of mass spectrometry-based proteomics and complex biological data analysis.
• Data Fluency: Proven experience working with high-dimensional omics datasets and statistical modeling approaches.
• Technical Stack: High proficiency in Python and/or R for advanced data analysis and visualization.

Preferred Assets

• Experience with affinity-based proteomics platforms or multi-omics data integration.
• Strong knowledge of biomarker discovery, translational research, and clinical development workflows.
• Experience developing customer-facing analytical tools or scientific software products.
• Familiarity with cloud-based data platforms and scalable analytics architectures.

Drive MS–Proteomics Data Integration Strategies

• Develop and demonstrate best practices for integrating MS and affinity-based proteomics datasets at both the data and biological interpretation levels.
• Design and execute analyses that showcase the immense value of combining orthogonal proteomics technologies.
• Generate scientific evidence demonstrating incremental biological insights, pathway enrichment, biomarker discovery, and predictive modeling performance from integrated datasets.
• Author scientific content, case studies, white papers, and data stories to communicate findings to both internal and external stakeholders.

Build Interoperability & Software Solutions

• Define technical requirements and use cases for integrating MS-derived results into our client's proprietary software platforms.
• Evaluate existing prototypes and collaborate with software development teams to design scalable, maintainable solutions.
• Lead implementation efforts for data ingestion, transformation, and harmonization workflows, focusing on converting MS outputs into compatible, streamlined formats.
• Partner with cross-functional stakeholders to ensure all developed solutions meet stringent customer and scientific standards.

Expand Analytical and Visualization Capabilities

• Enable advanced downstream analysis and visualization of MS data within the client's software ecosystem.
• Develop workflows supporting PCA, clustering, pathway analysis, differential expression analysis, sample stratification, and other exploratory analytics.
• Identify opportunities to leverage the client’s existing biological knowledge base and annotations to significantly enhance the interpretation of MS datasets.
• Validate analytical performance and optimize user experience through rigorous testing and customer feedback loops.