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Senior Expert Data Scientist, Predictive Safety (347486BR)

Technology

Data Analyst

Yearly

No

Cambridge, Massachusetts, United States

6000! That’s the number of associates in the Novartis Institutes for BioMedical Research (NIBR). This division is the innovation engine of Novartis, focusing on powerful new technologies that have the potential to help produce therapeutic breakthroughs for patients. The Pre-Clinical Safety (PCS) group in NIBR Translational Medicine provides world class preclinical safety profiling and assessment for optimal drug discovery, development and commercialization, with state-of-the-art regulatory compliance.<br><br>As a Senior Expert Data Scientist within the PCS Predictive Safety Data Exploration team, you will be responsible for advancing translational safety data science and driving drug development through partnership with the global PCS data science community, key Novartis R&D stakeholders and external collaborators. The job holder must have significant biology-based data science expertise, a broad scientific/technology knowledge base, and the ability to incorporate new scientific insights and internal/external innovation into strategic and practical initiatives. <br><br>Your responsibilities will include:<br>•Conceive, design, and execute translational safety data analyses spanning in silico, non-clinical and clinical studies, applying advanced analytical methods as required, generating high quality reports in a timely manner, and clearly communicating outcomes to stakeholders.<br>•Participate in and lead cross-functional safety data science collaborations with Discovery and Development partners to support the early derisking of compounds, drug targets, and therapeutic modalities, as well as the identification of potential safety monitoring and mitigation strategies<br>•Provide subject matter expertise for high-dimensional non-clinical and clinical safety data analyses (at chemoinformatic, molecular, biochemical, cellular, and physiologic levels) to inform predictive safety assessment strategies<br>•Work expeditiously as a member of matrixed project teams with diverse membership and expertise<br>•Provides matrix leadership, mentorship and training for team members, including potential supervision of PhD or Master students<br>•Undertakes general project management of data science work (planning, execution, monitoring, reporting, quality, compliance)<br><br>[#video#https://www.youtube.com/watch?v=FIxJdzIn0mE{#400,300#}#/video#]