Job Description

This is what you will do:

As an integral part of Alexions Bioinformatics and Data Sciences team you will lead the creation and application of novel data science solutions across the fields of Early Discovery, Target Identification/Validation, Translational Medicine, Clinical Development and Diagnostics. Your overall goal will be to advance Alexions rare disease portfolio and to better identify rare disease patients. You will join a highly skilled team which prides itself on creating strategic value and catalyzing change across Alexion through the innovative application of data sciences. You will need to effectively collaborate with other colleagues at Alexion with diverse scientific backgrounds to deliver novel quantitative solutions and analyses.

You will be responsible for:


Lead efforts to identify key needs and questions that can be addressed using genetics, Omics or other bioinformatics approaches in collaboration with crossfunctional research teamsDevelop and apply innovative data analysis techniques, including statistical analysis and AI/ML approaches to complex, disparate rare disease datasets, including drug target identification/validation and biomarker developmentPlan, execute, and iterate on data analyses in collaboration with experimental team to derive actionable insights through deep critical thinkingDevelop software tools and scripts to support data analysis and interpretation pipelinesPlay a crucial role in drug project and clinical teams to actively participate in scientific discussion and hypothesis generation and validation using computational techniques, and communicate regularly with research project teams and other key stakeholders to present findings, key next steps, and recommendations to ensure timely progressStay uptodate with relevant scientific literature and incorporate new insights into research activities and evaluation of new technologies and methods You will need to have: PhD (or equivalent degree) in computational biology, bioinformatics, human genetics, genomics, systems biology, bioengineering, or a related field, with strong background in data science and machine learning, 8+ years of related experience (including postdoc experience)Significant experience in drug target discovery and validation as well as biomarker analysis of multimodal data from preclinical/clinical researchProven track record in the analysis, visualization, and interpretation of genetics and Omics data Strong statistical analysis and programming skills in R and/or Python and familiar with Unix environment and highperformance computing environmentsStrong knowledge of human genetics, molecular biology, as well as biological pathways and networks Solid training and experience of machine learning/ artificial inteligence/ network modelingBe able to work independently within distributed team environment made of both internal and external stakeholders and contributors The ability to coordinate and pursue multiple simultaneous projects with tight deadlinesExcellent communication and presentation skills with specific experience in cross functional collaborations..The duties of this role are generally conducted in an office environment. As is typical of an officebased role, employees must be able, with or without an accommodation to: use a computer; engage in communications via phone, video, and electronic messaging; engage in problem solving and nonlinear thought, analysis, and dialogue; collaborate with others; maintain general availability during standard business hours. We would prefer for you to have: Familiarity with computational protein modeling and structural biology #LIDI1#LIHybrid

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