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Bioinformatics Engineer
2 months ago
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.
- 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.
- 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, 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.
- 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.