Novartis has one of the most exciting product pipelines in the industry today. A pipeline of innovative medicines brought to life by diverse, talented and performance driven people. All of which makes them one of the most rewarding employers in their field.
Post : Principal Scientist - Data Science (Preclinical Safety)
Job Description
Summary
The Preclinical Safety (PCS) department within the Novartis Biomedical Research Translational Medicine Unit provides world class preclinical safety profiling and assessment for optimal drug discovery, development and commercialization, with state-of-the-art regulatory compliance. As a Preclinical Safety Data Scientist, you will join our global PCS team to help us to unleash the power of data science for advancing translational safety assessment and to drive drug discovery and development. You will bring your curious, innovative, and collaborative mindset to leverage a wealth of non-clinical safety-related data generated within our department and use state-of-the-art machine learning (ML) methods and statistical techniques to accelerate the advancement of innovative medicines.
Key Responsibilities
Design and execute translational safety data analyses spanning in silico algorithms for toxicity prediction, in vitro toxicity screening assays, in vivo animal toxicology studies, and clinical safety outcomes, applying advanced analytical methods as required, and generating high quality reports in a timely manner
• Contribute to the unification, harmonization, and integration of legacy non-clinical safety-related data.
• Investigate new algorithms or modeling strategies, identify relevant research articles, and reproduce/apply innovative methodology to generate insights related to translational safety assessment.
• Quickly learn and pilot the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions.
• Participate in cross-functional safety data science collaborations with Novartis Biomedical Research partners to support the early derisking of compounds, drug targets, and therapeutic modalities
• Deliver clear and concise presentations for audiences with different expertise
• In collaboration with cross-functional partners, provide scientific and strategic input to support the early derisking of compounds, drug targets, and therapeutic modalities
• Ensure quality and compliance of data analyses and resultant reports.
Candidate Profile
• Advanced degree in a quantitative field (data science, machine learning, computer science, statistics) or life sciences, preferably with multidisciplinary background (chemoinformatics, bioinformatics, biomedical engineering, AI/ML in drug discovery or life sciences)
• PhD with 2+ years or MSc/MS/M.Pharm with 6+ years of relevant work experience; Strong understanding of statistics, machine learning and deep learning
• Demonstrated knowledge of data visualization and exploratory analysis; Knowledge of Python and machine learning/deep learning libraries.
• Experience with reproducible data science tools and practices. Previous research experience either in academia or industry
• Excellent communication skills and ability to translate analytical concepts for diverse audience and stakeholders (English is our primary language)
• Experience in the application of data science methods to drug discovery
• Experience with generative algorithms and explainable AI. Expertise in chemoinformatics, non-clinical ADME and/or toxicology is a plus.
• Team player
• Strives for continuous learning (scientific and technical)
Additional Information
Qualification : PhD with 2+ years or MVSc/MS/M.Pharm with 6+ years
Location : Hyderabad
Job ID : REQ-10004607
End Date : 20th June 2024
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