Pfizer Biomedical Data Engineer in Cambridge Kendall Sq. 610 Main, Massachusetts
The rapid growth of high-dimensional datasets at all levels of granularity together with broader availability of powerful computational methods offer new opportunities for science-based drug discovery. The Inflammation & Immunology research unit is capitalizing on this emerging science with an embedded computational group working in close collaboration with experimentalists.
If you are an applied research engineer/scientist with a passion for working on complex, high-dimensional datasets in biomedicine, then the Computational Systems Immunology group is the team for you. As a Biomedical Data Engineer, you will be an agile and core contributor in the research of impactful, data-driven problems in R&D.
The Biomedical Data Engineer's core mission is to integrate, organize, visualize and partially analyze heterogeneous omics scale datasets in conjunction with phenotypical and clinical data in a systematic, biologically plausible and scalable way. Data types will include RNASeq, genetics, FACS/cyTOF, single cell RNAseq, proteomics, electronic medical records as well as clinical and phenotypic data and will originate from many sources, including internal tech centers, clinical trial repositories, public omics data collections as well as disease-specific academic collaborations and consortia.
The successful candidate will have the passion and technical and biological know-how to establish practically useful solutions to coherently mine data for portfolio impact. In this role, a focus on modern technical infrastructure will be as important as a passion for data integrity and biologically plausible data modeling.
The role will be in close alignment with colleagues within the Systems Immunology function as well as project teams and partner lines to inform the I&I drug discovery pipeline and further the larger data infrastructure within Pfizer.
We also expect the successful candidate to communicate the value and efficiency of new data engineering capabilities, technologies, and research in order to advance adoption and awareness throughout R&D.
This position offers an opportunity to execute science-based drug discovery within one of the world's leading developers of human therapeutics, at the Pfizer Biomedical Institute based in the Cambridge Innovation Hub.
Design, establish, and continously elevate modern solutions to house heterogeneous omics and clinical data for ad-hoc queries, visualization, and sophisticated cross-modality analysis in the Inflammation&Immunology context.
Drive the biologically plausible modeling and integration of these data as a fundamental requirement for sophisticated systems analyses.
Work with heterogenous, high-dimensional data, crunching data for modeling, data mining, or analysis.
Lead partnerships with internal and external stakeholders in the data engineering space to further the development of Pfizer-wide data environments and the timely integration of high value datasets.
Provide technical leadership, driving and performing best engineering practices to initiate, plan, and execute cross functional research projects.
Masters or Ph.D. in Computer Science, Statistics, Computational Biology, Bioinformatics or related technical discipline, or related practical experience. MS + 5 years of relevant work experience, or PhD + 2 years of relevant work experience is desirable.
Experience in designing and building infrastructure at scale and 4+ years experience programming experience in Java, C/C++, Python and/or Scala.
Expertise in handling multi-omics (genomics, transcriptomics, proteomics, etc.) and / or clinical data preferred.
Passion and curiosity for data and proven ability to take ideas from research to production.
Curiosity about biological and pathological processes and mechanisms, esp. with an immunological and inflammatory focus.
Expertise in one or more of the following: omics data analysis, machine learning, computational statistics, information retrieval, or natural language processing.
Additional desired skills and experience:
Iterative, test-driven development and continuous integration.
Configuration management (SVN, ant, maven, etc.; git preferable).
Developing and designing consumer-facing products.
Hadoop, Pig, or other MapReduce paradigms and familiarity with other distributed frameworks, such as Apache Spark
Knowledge of relevant public and proprietary databases, methods and tools in the omics and clinical space.
Published work in academic conferences or industry circles. Candidates may be invited to present a talk on their work as part of the interview process.
EEO & Employment Eligibility
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Eligible for Relocation Package
Eligible for Employee Referral Bonus
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