Clinical Data Scientist

Found in: beBee jobs US - 3 weeks ago

South San Francisco, California, United States ESSA Pharma Full time

ESSA Pharma Inc., a clinical-stage company, is seeking a talented and motivated scientist to join our vibrant team as a Bioinformatician. ESSA pharma is a virtual company with substantially all of its work outsourced to CROs.

The job demands a knowledge of oncology and/or statistical analysis, machine learning as well as cutting-edge tools and techniques in bioinformatics.

The ideal candidate will thrive when integrated into project teams and is expected to provide solutions and insights to preclinical, translational and clinical programs from a computational biology point of view, e.g. helping with experimental design, data analysis and statistical interpretation that will lead to the generation and/or validation of new hypotheses.

A deep knowledge of NGS technologies and methods, statistical analysis, machine learning and excellent programming skills in Python and/or R is essential for this role.

The candidate must be comfortable working independently and collaborating and communicating with scientists at all levels and across disciplines.

Responsibilities include but are not limited to:

  • Provide computational biology support for discovery biology, translational research and clinical biomarker studies
  • Develop and implement bioinformatic algorithms for integrative analysis and visualization of multi-omics data from various sources and data modalities such as bulk or single-cell RNA-Seq, WES, proteomics and other biomarker signals from serum, blood and tissue biopsies
  • Develop web applications such as R Shiny and/or Python Streamlit to make complex analysis pipelines and database queries accessible to non-bioinformatic scientists

    Position Qualifications:
    • PhD in bioinformatics, computational biology, genomics, statistics, computer science or a related discipline is required
    • At least two years of postdoc or industry experience are strongly preferred but not essential
    • Must have experience working with large genomic data sets, planning NGS experiments and analysis
    • Experience in analyzing and integrating multi-omics bulk and/or single-cell datasets is strongly preferred
    • Proficiency in programming languages such as R and/or Python is required
    • Working knowledge of machine learning algorithms, exploratory data analysis and statistical modeling and techniques is required
    • Excellent communication (oral and written) skills, interpersonal skills, and cross-functional teamwork are essential
    • Must be comfortable handling multiple concurrent fast paced projects
    • Experience in predictive/response biomarker identification and translational research with applications in patient datasets and/or clinical trials would be a significant plus

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