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Bioinformatics Engineer

2 months 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 Bioinformatics Engineer, you will play a critical role in developing and maintaining large-scale bioinformatics pipelines for the ingestion, management, and analysis of biological datasets.

Key Responsibilities

  • Design, develop, and maintain large-scale bioinformatics pipelines for the ingestion, management, and analysis of biological datasets, particularly omics, imaging, and clinical data.
  • Work with other engineers and scientists to build Isos platform applying AI to biological systems.
  • Perform data analysis and data quality assurance according to best practices.
  • Design and develop representations, models, and computational modules for biological data optimized for AI research and production.
  • Contribute to the wider development of Isos data and computational platform, working with other engineers to architect, build, and operate the platform's components.
  • Work with other members of the data engineering team to ensure the quality, integrity, and scalability of data and pipelines.
  • Partner and collaborate with a diverse set of 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.
  • Experience building scalable systems for the ingestion and preparation of large-scale datasets.
  • Strong knowledge of bioinformatics tools and methodologies and familiarity with the analysis of large biological datasets, such as omics, imaging, and clinical data.
  • Experience working with common bioinformatics datasets and data repositories, such as NCBI, Cosmic, ClinVar, UK Biobank, TCGA, dbSNP, and OMIM.
  • 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/trajectory and a passion for learning.
  • Either a BSc/MSc degree in Bioinformatics, Computer Science, 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.