Data Scientist, Proteomics

Vor 6 Tagen

Basel, Schweiz Monte Rosa Therapeutics, Inc Vollzeit

Overview:
We are seeking a highly skilled Data Scientist specializing in massspectrometry-based proteomics to join our data science team. In this role, you will leverage advanced analytical techniques to extract meaningful insights from complex proteomics datasets generated by state-of-the-art mass spectrometry techniques. You'll play a crucial role in accelerating our molecular glue discovery platform by developing robust data science workflows that bridge high-throughput screening data with biological understanding.

**Responsibilities**:

- **Proteomics Data Analysis**: Analyze large-scale DIA and DDA shotgun-proteomics datasets to identify differential expression patterns and elucidate molecular mechanisms
- ** Algorithm Development**: Design and implement algorithms and statistical models to process, quality control, and interpret complex proteomics data
- ** High-Throughput Screening Support**: Develop automated pipelines for analyzing LC-MS data from high-throughput screening campaigns to identify novel molecular glue targets and mechanisms
- ** Data Integration**: Integrate proteomics data with other omics datasets, chemical structure data, and biological pathway information to generate actionable insights
- ** Visualization & Reporting**: Create data visualizations and comprehensive reports for cross-functional teams including medicinal chemistry, biology, and clinical development
- ** Method Development**: Collaborate with analytical chemistry teams to optimize data acquisition and develop computational approaches for proteomics data analysis
- ** Platform Enhancement**: Contribute to the continuous improvement of our molecular glue discovery platform through innovative data science methodologies

Qualifications:

- PhD or MS in Data Science, Computational Biology, Bioinformatics, Physics, Chemistry, or a related quantitative field, with publications in computational proteomics, chemoproteomics, or chemical biology.
- A minimum of 2+ years industrial hands-on experience in proteomics data analysis
- Knowledge of SQL and R, or other data analysis tools
- Proficiency in Python programming with experience in data science libraries (pandas/polars, numpy, scipy, scikit-learn, matplotlib/seaborn/plotnine/ggplot)
- Experience with cloud computing platforms (AWS, GCP) and containerization technologies
- Demonstrated experience working with LC-MS or other omics data, particularly in high-throughput screening (HTS) environments
- Strong foundation in core data science concepts including statistical analysis, machine learning, data visualization, and experimental design
- Strong foundation in mass spectrometry data processing software algorithms (identification, quantification, missing value imputation, differential expression)

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