Genetic Data Analyst (The Genome Decoder)

Unreal Gigs
Cambridge
1 year ago
Applications closed

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Are you passionate about unlocking the secrets hidden in the human genome? Do you have a knack for analyzing complex genetic datasets to uncover meaningful insights that drive advancements in personalized medicine, genomics research, and biotechnology? If you’re excited about turning raw genetic data into actionable knowledge that can change the future of healthcare,our clienthas the ideal role for you. We’re looking for aGenetic Data Analyst(aka The Genome Decoder) to help analyze, interpret, and manage large-scale genomic datasets that provide valuable insights into human health, disease, and genetic variation.

As a Genetic Data Analyst atour client, you’ll collaborate with bioinformaticians, geneticists, and researchers to make sense of vast genomic datasets. You’ll play a key role in analyzing sequencing data, identifying genetic variants, and developing data-driven solutions that improve precision medicine, drug development, and clinical diagnostics.

Key Responsibilities:

  1. Analyze and Interpret Genomic Data:
  • Perform in-depth analysis of genomic and genetic data, including DNA sequencing (NGS), RNA-seq, and whole-genome sequencing datasets. You’ll identify genetic variants, mutations, and biomarkers that are critical for research and clinical applications.
Develop and Maintain Data Pipelines:
  • Build and manage data analysis pipelines that automate the processing of large-scale genetic datasets. You’ll ensure that these pipelines are efficient, scalable, and able to handle complex data from multiple sources, including high-throughput sequencing technologies.
Collaborate with Geneticists and Researchers:
  • Work closely with geneticists, bioinformaticians, and clinical researchers to translate genomic data into actionable insights. You’ll support their research by providing detailed data analysis, statistical interpretation, and visualization of genetic findings.
Perform Statistical and Bioinformatics Analyses:
  • Apply statistical techniques and bioinformatics tools to analyze genetic data, identify significant patterns, and validate findings. You’ll use tools like R, Python, Bioconductor, and other bioinformatics software to extract meaningful insights from raw data.
Support Precision Medicine Initiatives:
  • Contribute to precision medicine projects by identifying genetic variants associated with diseases, drug responses, and hereditary conditions. You’ll help develop personalized treatment plans and therapies based on individual genetic profiles.
Visualize and Report Data Insights:
  • Create visualizations, reports, and presentations that communicate complex genetic data clearly and effectively. You’ll use data visualization tools to present findings to non-technical stakeholders, including clinical teams and research collaborators.
Ensure Data Quality and Integrity:
  • Implement robust data quality checks to ensure the accuracy, reliability, and reproducibility of genetic analyses. You’ll work to maintain data integrity across different stages of analysis and ensure that results meet high scientific standards.

Requirements

Required Skills:

  • Genomics and Bioinformatics Expertise:Extensive experience in analyzing and interpreting genomic data, including whole-genome sequencing (WGS), exome sequencing, RNA-seq, and other high-throughput sequencing datasets. You’re familiar with common genetic analysis tools and databases (e.g., GATK, VEP, dbSNP).
  • Programming and Data Analysis:Proficiency in programming languages like Python, R, or Perl for data analysis and pipeline development. You’re skilled in applying statistical methods to large genetic datasets and interpreting results.
  • Data Visualization and Reporting:Experience using data visualization tools like ggplot2, Matplotlib, or Seaborn to present genetic data in an intuitive and accessible manner. You can create clear, actionable reports based on your findings.
  • Variant Calling and Annotation:Experience with variant calling, annotation, and interpretation, including knowledge of SNPs, indels, and structural variants. You’re familiar with tools like GATK, ANNOVAR, and SnpEff for variant analysis.
  • Collaboration and Communication:Strong collaboration skills with the ability to work cross-functionally with geneticists, bioinformaticians, and clinical researchers. You can explain complex genetic data in a way that is understandable to both technical and non-technical audiences.

Educational Requirements:

  • Bachelor’s or Master’s degree in Genetics, Bioinformatics, Computational Biology, or a related field.Equivalent experience in genetic data analysis or bioinformatics is highly valued.
  • A Ph.D. in Genetics, Genomics, or Bioinformatics is a plus but not mandatory.
  • Certifications or additional coursework in bioinformatics tools, statistical genetics, or data science are advantageous.

Experience Requirements:

  • 3+ years of experience in genetic data analysis,with hands-on experience analyzing large-scale genomic datasets.
  • Proven experience with next-generation sequencing (NGS) data analysis, including whole-genome and exome sequencing.
  • Experience working on projects in clinical genetics, precision medicine, or genomics research is highly desirable.

Benefits

  • Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
  • Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
  • Work-Life Balance: Flexible work schedules and telecommuting options.
  • Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
  • Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
  • Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
  • Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
  • Tuition Reimbursement: Financial assistance for continuing education and professional development.
  • Community Engagement: Opportunities to participate in community service and volunteer activities.
  • Recognition Programs: Employee recognition programs to celebrate achievements and milestones.

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