Posted on Apr 5, 2021 by Alexion Pharmaceuticals
Alexion is seeking a talented Bioinformatics Scientist to join Alexion's Data Sciences, Genomics, and Bioinformatics (DGB) team which focuses on the the design, building, and deployment of novel bioinformatic solutions spanning Early Discovery, Target Identification, Translational Medicine and Diagnostics. These solutions have included in the past a graph-database of the entire rare-disease landscape annotated with prevalence, severity, clinical trial options, and genetic signature; a genomics-based rare-disease patient prevalence platform to inform licensing/acquisition opportunities; and an AI-based phenotype- and genome-driven rare-disease diagnosis decision-support systems. The candidate will need to effectively collaborate with other colleagues at Alexion with diverse scientific backgrounds to deliver novel quantitative solutions and analyses.
Job Duties & Responsibilities
Apply state of the art and innovative approaches to handling disparate life sciences datasets
Interface with Antibody Engineering, Target Identification, Biomarker, Biostatistics, Epidemiology and Clinical Development teams collaboratively define solutions and/or answer questions
Conduct end-to-end data analysis from a variety of disparate life sciences datasets through transformations producing impactful visualization and reporting the findings analysis
Design and Implement novel machine learning workflows and algorithms on unstructured, disparate data sets
Develop software tools and scripts at scale to support data analysis and interpretation pipelines.
Present and discuss findings with project teams, support iterative solutions development and scientific research.
Integrate and summarize large-scale data and information across multiple scientific, translational, and clinical domains.
Take a hands-on role and deliver on highly visible multiple projects
Rapidly identify and prototype methods and visualizations to answer key business questions
Communicate effectively with team members, experts and regulatory authorities.
Inspire others on culture change
PhD degree in computational biology, bioinformatics, computer science or a related field, with strong background in data science and machine learning
2+ years of hands-on bioinformatics experience in an academic, industry, or government setting with a strong record of accomplishments and project delivery.
Strong knowledge of human genetics, molecular biology, as well as biological pathways and networks
Proven experience in software development such as Java, Python, C/C++, etc.
Expert knowledge of statistical analysis packages like R, SAS or similar.
Familiarity with concepts, tools and data formats used for sequence analysis, protein structure modeling and integration of diverse -omics datasets
Strong enthusiasm and curiosity about the intersection of biology, data and technology
Be able to work independently within distributed team environment made of both internal and external stakeholders and contributors
Demonstrated ability to handle multiple priorities
Excellent communication and presentation skills with specific experience in cross functional collaborations.
Familiarity with cloud computing services and its service offerings
Familiarity with data visualization tools and dimensionality reduction
Proficiecy in building end-to-end data analysis workflows (eg KNIME, Cromwell)
Familiarity in the use of controlled clinical terminologies and ontologies (UMLS, SNOMED, ICD, etc)
Familiarity in the use of rare disease and scientific controlled terminologies and ontologies (ORDO, OMIM, HPO, GO, etc.)
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