Role Summary
Senior Computational Biologist / Data Engineer role focused on combining data science tools with biological knowledge to perform exploratory data analyses, curate high-quality datasets, build efficient data workflows, and apply automation and AI to ensure accuracy and scalability in data systems. Location: Basel, Switzerland or Cambridge, MA, US. Full time, hybrid.
Responsibilities
- Collaborate with cross-functional teams to curate key experimental and omics datasets with an emphasis on quality and correctness to ensure that our complex scientific data are trustworthy
- Perform exploratory data analyses on key experimental and omics datasets
- Evaluate and implement automation tools and AI/ML approaches to enhance data curation and EDA workflows that increase the speed and accuracy of data handling
- Collaborate with cross-functional teams to develop and adopt best practices for data engineering
Qualifications
- Ideally an advanced degree (PhD, MS, or BS) in Computational Biology, Bioinformatics, Data Science, Computer Science, or related field with relevant experience
- A minimum of 5-8 years in either academia or industry working in an equivalent position in computational biology, bioinformatics, data engineering, or related field
- At least 4-5 years of experience working with molecular biology or omics data
- Demonstrated statistical and analytic rigor while performing exploratory data analyses and drawing scientific conclusions from experimental data (e.g., scRNAseq, RNAseq, ChIPseq, DNAseq, proteomics, compound screens, or CRISPR screens)
- Fluent in one or more programming languages with bioinformatics applications (R, Python)
- Knowledge of version control, reproducible workflows, Unix / Linux
- Curiosity, creativity, strong organizational skills, solution-oriented problem solving
- Ability to work independently, prioritize tasks, determine project next steps, manage multiple projects and stakeholders simultaneously
- Excellent written and verbal communication skills, including the ability to explain complex concepts to diverse audiences