it pharma AstraZeneca is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we are more than one of the world's leading pharmaceutical companies. At AstraZeneca, we are proud to have a unique workplace culture that inspires innovation and collaboration through scientific research. Here, employees are empowered to express diverse perspectives and are made to feel valued, energized and rewarded for their ideas and creativity. About the role You will work as member of the expanding Dynamic Omics group and be actively involved in developing and implementing pipelines for metabolomics and proteomics applications to support the analysis of preclinical and clinical samples. This position, sitting in Gaithersburg, MD, will be primarily focused on getting insight from large-scale omics data investigating a number of biological questions in support of our preclinical and clinical research and requires comprehensive expertise in omics data interpretation. You must be passionate and enthusiastic about omics data and possess fundamental understanding of mass spectrometry-based omics data. You will be responsible for writing scripts and develop tools to analyze, integrate and visualize complex data sets. You will analyze quantitative mass spectrometry proteomics and metabolomics data for untargeted and targeted omics experiments. You will understand quantitative proteomics and metabolomics workflows and data structure to efficiently integrate and/or develop automated data acquisition, processing, analysis and visualization protocols, with appropriate infrastructure and pipeline management tools. You will develop appropriate QC tools to monitor and improve data acquisition. You will be responsible for maintaining and developing our applications for omics insight. You will contribute to local and global data management processes and solutions for capturing and exploiting omics and other high-dimensional data types such as transcriptomics and genomics. You will effectively collaborate with biologists, bioinformaticians, statisticians and other data scientists to design and deliver robust and impactful multiomics studies, via data processing, analysis and interpretation. This includes design of experiments, analysis of omics data in conjunction with other data types via statistical, multivariate and machine learning approaches. You will combine open-source and/or commercially available software platforms for enabling protein and metabolite identification & annotation across multiple biosamples (cell lines, body fluids, tissues). In addition, this role will work closely together with other bioinformaticians and data scientists primarily focused on developing the infrastructure for automated data processing. Finally, this position will closely collaborate with scientists in the Proteomics and Metabolomics, Transcriptomics, Flow Cytometry and Imaging groups and support Translational Scientists. Give the scope of this dynamic role and the need to multitask, it is essential to be a fast learner, excellent communicator, well organized, innovative and able to work independently when designing and executing experiments as well as to manage and prioritize tasks. Furthermore, you should demonstrate enthusiasm, motivation, attention to detail and willingness to learn new technologies, flexibility and confidence. Essential Requirements As a Senior Bioinformatician your skills and qualifications will ideally include: + PhD in bioinformatics, mathematics, computer science, statistics, engineering or the life sciences with 4 - 10 years of experience in mass spectrometry-based omics data analysis + Demonstrable experience in the core competency areas: Mass-spectrometry based omics, multivariate and/or high dimensional data analysis (-omics), data management and visualization + Experience with relevant software tools such as Python, R, Perl, Shiny, Javascript, C/C++, SQL/NoSQL databasing, networked and cloud-based systems, software versioning tools (eg Git/Github) + Experience with issues related to normalization, imputation and analysis of LC-MS omics data + Contribute innovative and novel scientific analyses across line platform projects + Basic understanding of molecular biology, cell biology, and human physiology + can communicate and collaborate effectively with scientists across a broad range of disciplines Desirable Requirements + Experience in multi-omics integration would be advantageous + Prior supervisory experience of 1-2 junior bioinformaticians would be advantageous.