Computational Scientist, NGS Data Analysis

    Computational Scientist NGS Data Analysis

    Website Altos Labs

    Job Profile: Computational Scientist, NGS Data Analysis

    Job ID: 257

    Location: San Francisco Bay Area, CA

    Date Posted: 16 June 2022

    Our Mission

    Our mission is to restore cell health and resilience through cellular rejuvenation programming to reverse disease, injury, and the disabilities that occur throughout life.

    For more information, see our website at

    What We Want You to Know

    We want our employees to bring their whole selves to work and be recognized for the talents, perspectives, and unique life and career experiences they bring. We are a culture of collaboration and scientific freedom, and we believe in the values of diversity, inclusion and belonging to spur innovation.

    What You Will Contribute to Altos

    The Bay Area Institute of Science at Altos Labs has an opening for a Computational Scientist in our MultiOmics Data Analysis group. Responsibilities include:

    • Collaborate closely with domain knowledge experts to plan and design studies to elucidate molecular phenotypes of cellular health, rejuvenation and reprogramming
    • Develop NGS analysis pipelines covering raw data processing, through to  exploratory and statistical data analysis, to hypothesis generation
    • Develop new and apply existing methods for multi-omic data integration
    • Perform integrative analyses of omics and diverse phenotypic data
    • Present and interpret analysis results to inform future experiments and to guide decision making
    • Embed analyses and visualizations in automated reports
    • Build interactive dashboards for data visualization and exploration
    • Partner with other computational scientists to establish automated, robust and efficient analytical pipelines for reproducible research
    • Stay current with and adopt emergent analytical methodologies, tools and applications to ensure fit-for-purpose and impactful approaches

    Who you Are

    Minimum Qualifications:

    • PhD in a quantitative field (e.g. mathematics, bioinformatics, physics) with significant biological background OR a Life Sciences degree with significant computational experience
    • Advanced understanding of NGS platforms and the underlying technological limitations
    • Extensive experience with building NGS data analysis pipelines (RNA-seq, Ribo-seq, ATAC-seq, BS-seq, Perturb-seq)
    • Extensive knowledge of standard tools for analysis of NGS data ( e.g. FastQC, BWA, BEDtools, STAR, TopHat, Cufflinks, Limma, edgeR, DESeq)
    • Proficiency in Python and/or R. Hands-on skills using data science packages ( for instance, Pandas, Scikit-learn, NumPy, Tidyverse, Caret)
    • Statistical analysis background (e.g. parametric and non-parametric tests for differential expression analysis, enrichment analysis, clustering, dimensionality reduction techniques, power analysis)
    • Excellent communication skills. Ability to present complex computational methods to non-experts.
    • Established ability to translate biologists/project team’s scientific questions into analytical strategies and methods
    • Strong collaboration skills and ability to work as part of a team in an international and interdisciplinary environment
    • Outstanding organizational skills and the ability to work independently

    Preferred Qualifications:

    • Experience with technologies required to undertake analyses on large data sources or with computationally intensive steps (databases, parallelization, Hadoop, Spark, etc.)
    • Experience with code management and collaboration platforms (e.g. GitHub, Bitbucket)
    • Experience with development of visualization reports and apps (e.g. Shiny/Dash/ d3)
    • Experience with applying machine learning to mine biological datasets for actionable hypotheses
    • Experience with software development
    • Experience with cloud computing

    Job ID 257


    Altos currently requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions (e.g., due to a medical condition or sincerely-held religious belief).

    Thank you for your interest in Altos Labs where we strive for a culture of Scientific Freedom, Learning and Belonging.

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