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Principal Scientist, Computational Biology

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Job Description

Cool video about Senda Bio: https://vimeo.com/540232673

The Position

As a key member of the Senda Biosciences Discovery Platform group, the Computational Biology Principal Scientist will enable Senda’s pioneering work of unlocking inter-systems biology for human health. Working as part of a cross-disciplinary team of biologists, engineers, data scientists, and chemists, the candidate will develop and apply computational methods that support Senda’s efforts to leverage and enhance Senda’s unique drug discovery engine.


  • Serve as an integral member in a cross-disciplinary team driving the development and advancement of Senda’s discovery engine, helping to establish new therapeutic area programs
  • Lead computational support for key discovery program/efforts
  • Develop new methodologies to facilitate the discovery of novel therapeutic targets, bioactives, and biomarkers
  • Operate and enhance existing computational ‘omics data workflows
  • Contribute to the culture of scientific excellence at Senda

Required Experience

  • PhD in Computational Biology, Bioinformatics, or a related field with 2+ years of experience in industry
  • Proficiency in a relevant programming language (g. Python, R) and standard command line tools
  • Demonstrated success leading the computational portion of a multi-member project
  • Demonstrated success balancing multiple simultaneous computational efforts
  • Demonstrated ability to process and integrate multiple types of ‘omics data to derive biological insights
  • Foundational understanding of common methodologies employed in ‘omics data analysis, especially metabolomics and metagenomics
  • Firm grasp of modern statistical methods and application to high dimensional datasets
  • Ability to clearly communicate methods and findings to colleagues with varying levels of technical expertise
  • Knowledge of and experience applying best practices in data science
  • Comfort working in and developing in a cloud-based environment (AWS, Google Cloud)

Preferred Experience and Qualifications

  • Experience exploring biological interactions between species
  • Demonstrated experience building and using machine learning models to push forward research in the life sciences
  • Knowledge of metabolic-pathway-oriented analysis methods and experience predicting or annotating enzyme functions
  • Excellent documentation and experience with version control, containerization and workflow management solutions such as Nextflow, Snakemake, Airflow, or Luigi
  • Ability to thrive in a driven organization with evolving goals and deliverables

  • Personal Characteristics:
    • Pioneering: We create bold innovations leveraging insights in intersystem biology
    • Science Driven: We apply exceptional science to bring breakthrough medicines to patients
    • Authentic: we embrace the importance of honesty, accountability, transparency and openness
    • Collaborative: We succeed when we shared knowledge, expertise, and experiences to develop revolutionary medicines