Bioinformatics Engineer

2 weeks ago

London, Greater London, United Kingdom Lifelancer Full time
About the Role

We are seeking a highly skilled Bioinformatics Engineer to join our data engineering team at Lifelancer. As a key member of our team, you will play a crucial role in building and maintaining our cutting-edge bioinformatics platform.

Key Responsibilities
  • Design, develop, and maintain large-scale bioinformatics pipelines for the ingestion, management, and analysis of biological datasets.
  • Collaborate with engineers and scientists to build our Isos platform, applying AI to biological systems.
  • Perform data analysis and quality assurance according to best practices.
  • Develop representations, models, and computational modules for biological data, optimized for AI research and production.
  • Contribute to the development of our data and computational platform, working with other engineers to architect, build, and operate platform components.
  • Partner with diverse teams, including Computational Biology, ML research, product, business development, and operations.
  • Provide documentation, guidance, and communication on bioinformatics to the wider organization.
Requirements
  • Experience in bioinformatics, with a focus on data engineering and pipeline development.
  • Strong knowledge of bioinformatics tools and methodologies and familiarity with the analysis of large biological datasets.
  • Experience working with common bioinformatics datasets and data repositories.
  • Programming and software engineering skills in a language such as Python, Java, Scala, C/C++, or Go.
  • Knowledge of data management tools and technologies, including ETL frameworks, database engines, and file and object stores.
  • Some exposure to cloud environments.
  • Demonstrate ongoing career progression and a passion for learning.
  • Either a BSc/MSc degree in Bioinformatics, Computer Science, or a related technical field, or equivalent practical experience.
Nice to Have
  • A PhD in Bioinformatics, Computer Science, or a related field.
  • Exposure to machine learning and experience building machine learning systems.
  • Experience working with life science ontologies.
  • Exposure to data curation.
  • Experience with data governance and data lifecycle management.
  • Knowledge of the pharmaceutical industry, ideally with a focus on drug discovery.
  • Experience building, deploying, and maintaining production systems on GCP.
  • Strong experience in Python.
  • Experience in statistical analysis and data visualization.

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