Job Description Summary

Internal Job Title: Senior Expert I, Data Science

Role Location: Basel, Switzerland

About this role:

Novartis Biomedical Research is our innovation engine where public and private research merge to substantiate novel drug candidates and evaluate novel biomedical technologies to make medicine. We are seeking a creative and collaborative investigator practiced in wet and dry lab research to join our mission to develop transformative new therapies for patients with chronic and acute renal diseases.

The successful candidate will work at the cutting edge of applied data science to model and test important priorities in translational research. Your participation on project teams will require iterative mining and modeling complex, multi-modal data to drive drug discovery and early development. As a member of Novartis, the successful candidate will participate in a global community with extensive know-how and resources in data analysis, data engineering, machine learning, experimental techniques and resources to test biomedical hypotheses derived from computed models. As a member of the Translational Research & Data Science group in DAX, your role as Senior Expert Data Scientist I will leverage your experience and knowledge in general medicine unmet needs, especially renal maladies.

Job Description

Key Responsibilities:

• Applying established and novel approaches to model multi-modal clinical data to identify biomarkers predictive of disease progression and treatment response, and to nominate novel therapeutic target hypotheses
• Developing and applying a portfolio of pre-clinical models derived from internal and public data to departmental projects
• Working closely with a core team of Translational Research & Data Science scientists fluent in wet and dry lab practices
• Actively participate on interdisciplinary teams to model biology and guide impactful decision-making in drug discovery and early development
• Actively participate in alliances with external partners at top healthcare institutions, including the opportunity to publish your findings

Essential Requirements:

• PhD or equivalent life sciences industry experience modeling biomedical research data
• Demonstrated working knowledge and application of statistics and data modeling to large scale life-sciences data
• Hands-on experience in integration of large multi-omics data (genomics, transcriptomics, proteomics and metabolomics) to answer key scientific questions related to precision medicine and understanding disease
• Hands-on industry experience with clinical data and its responsible handling
• Proficiency in R/Python and competency working in a Linux environment
• Reproducible research practitioner with demonstrated visualization and reporting skills
• A team-oriented, practical approach to problem solving

Desirable Requirements:

• A commitment to prioritising patient unmet medical needs
• A commitment to alignment with departmental priorities
• Strong written and oral communication skills

Why Novartis: Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture

Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture

Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network

Skills Desired

Apache Hadoop, Applied Mathematics, Big Data, Curiosity, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling