Bioinformatics Data Scientist
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Job Description
We are seeking a highly analytical and innovative Bioinformatics Data Scientist to join our interdisciplinary team. In this role you will integrate advanced computational methods machine learning and bioinformatics techniques to analyze complex biological datasets and extract actionable insights. Your work will directly contribute to the development of precision medicine novel therapeutics diagnostics or agricultural biotechnology solutions.
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Key Responsibilities:
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Design and implement computational workflows for processing and analyzing large-scale omics data (e.g. genomics transcriptomics proteomics epigenomics).
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Apply statistical modeling and machine learning to uncover patterns biomarkers or therapeutic targets.
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Integrate data from multiple sources (e.g. public datasets clinical data lab experiments) to generate comprehensive biological insights.
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Develop visualization dashboards and reports to communicate findings to technical and non-technical stakeholders.
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Collaborate with biologists clinicians and software engineers to support ongoing research and product development.
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Contribute to publications patents and regulatory documentation as applicable.
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Ensure reproducibility scalability and maintainability of all developed code and pipelines.
Qualifications:
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Masters or Ph.D. in Bioinformatics Computational Biology Data Science Computer Science or a related field.
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25 years of experience working with biological datasets in an industry or academic setting.
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Strong programming skills in Python and/or R; familiarity with data science libraries (e.g. pandas scikit-learn TensorFlow ggplot2).
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Experience working with high-throughput sequencing data (e.g. RNA-Seq WGS scRNA-Seq) and tools (e.g. GATK DESeq2 STAR Seurat).
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Proficiency in statistics machine learning and data visualization.
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Experience with version control (Git) cloud computing (AWS GCP) and workflow tools (e.g. Nextflow Snakemake).
Preferred Skills:
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Experience with AI/ML approaches for biomarker discovery or drug response prediction.
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Familiarity with relational databases and APIs for biomedical data (e.g. TCGA ENCODE GEO EGA).
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Background in molecular biology or translational research is a plus.
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Experience in clinical bioinformatics or regulatory environments (e.g. FDA HIPAA-compliant systems).
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Employment Type
Full Time
