Data Scientist - Bar Harbor, United States - The Jackson Laboratory

    The Jackson Laboratory
    The Jackson Laboratory Bar Harbor, United States

    2 weeks ago

    Default job background
    Full time
    Description
    The Chesler lab is seeking a Data Scientist to develop algorithms and computational resources to analyze and interpret mouse genomic and phenotypic data. The Data Scientist will work with scientists to understand biomedical questions, develop algorithmic approaches to address them, implement those approaches with well-documented code, report and interpret results, and work with software engineers to harden pipelines into software products. The Data Scientist will deliver these reproducible analytical products, including visualizations, pipelines, and data resources that help researchers answer biomedical questions. They will also work cross-functionally and collaborate with a team of scientists, curators, bioinformaticians, data scientists, and software engineers to maintain and enhance knowledge extraction for cross-species analyses. Key Responsibilities & Essential Functions
  • Design, develop, implement, and test novel algorithms and software for genomic and cross-species analyses
  • Conduct robust statistical analysis of biomedical data and generation of visualizations, reports and summaries
  • Effectively communicate and collaborate in cross-functional teams that include members with diverse expertise e.g., biologist, neuroscientist, curator, software engineer
  • Work independently and efficiently to lead the development of analytical products and data resources
  • Lead internal and external presentations to both computational and non-computational scientists. Prepare codebase and write manuscripts for publication;
  • Quality control of both low- and high-dimensional datasets, design and implement quality control and quality assurance procedures to confirm the accuracy, fidelity and completeness; troubleshoot data exports and data uploads; track data exports and follow through; implement bulk data corrections
  • Participate in software tool maintenance, development and deployment.
  • Proactive identification of opportunities to improve practices, streamline analysis, and maximize data value.
  • Qualifications
  • B.S. in Computer Science, Bioinformatics, Statistics, Data Science or related field is required. MS/PhD is preferred
  • At least 2 years of relevant experience
  • Solid understanding of experimental design, core statistical methods, and machine learning tools
  • Experience with algorithm development in areas such as machine learning, genomics, and statistics. Experience hardening analytical products into software is a plus.
  • Prior experience analyzing mouse genomic and phenotypic data is essential. QTL analysis a plus
  • Proficient in R and/or Python
  • Experience in working with high-performance clusters and/or cloud computing environments. Experience creating Nextflow pipelines and singularity containers a plus
  • Experience in version control tools
  • Ability to interpret scientific literature and apply relevant concepts in fields related to current projects
  • Ability to lead projects/tasks, self-manage timelines, and work independently with limited supervision is essential
  • Demonstrated ability to effectively communicate with non-computational stakeholders is essential
  • The salary range is $73,305 - $122,730. Salary will be determined based on qualifications and experience.

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    About JAX:

    The Jackson Laboratory is an independent, nonprofit biomedical research institution with a National Cancer Institute-designated Cancer Center and nearly 3,000 employees in locations across the United States (Maine, Connecticut, California), Japan and China. Its mission is to discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.

    Founded in 1929, JAX applies over nine decades of expertise in genetics to increase understanding of human disease, advancing treatments and cures for cancer, neurological and immune disorders, diabetes, aging and heart disease. It models and interprets genomic complexity, integrates basic research with clinical application, educates current and future scientists, and provides critical data, tools and services to the global biomedical community.