\\nJob Description

Location: Basel, Switzerland.

We are seeking a dedicated, creative, and skilled data scientist to join our global, dynamic, agile, embedded \\\'dry-lab\\\' research environment and enable the discovery of therapeutic targets and new medicines for diseases of aging. As part of the Disease of Aging and Regenerative Medicine (DARe) Data Science team, you will have the opportunity to drive the integration and mining of high dimensional biological data using internal and external data resources. As a member of the NIBR data science community, you will also benefit from a >200 people global community with extensive know how and resources in data analysis, data engineering and machine learning.

Key responsibilities:

Conduct data extraction, curation, integration, and mining of multi-modal high dimensional biological data to provide actionable insights.
Develop and maintain innovative data I/O, analytical tools, and pipelines.
Work at the interface between in vitro biology investigators, integrated pharmacology, informatics experts and other data scientists globally to deliver new and actionable hypotheses based on large-scale molecular, imaging, and real-world evidence biomedical data.
Contribute to the identification of the most promising new analytical methodologies and data solutions and implement/integrate them within the DARe data science analytic toolbox.
Identify novel therapeutic targets and biomarkers candidates, elucidate the mode of action of drug candidates, advance the understanding of the molecular cross talks involved in cell fate decision and disease trajectories.

Minimum requirements

What You\\\'ll Bring:

PhD with 1-2 year or MS with 4+ years relevant experience in bioinformatics, computer science, data science or field requiring intense data wrangling and analysis.
Outstanding Programming skills in Python and R with experience of static and interactive reports and visualizations (RMarkdown, R shiny, Plotly, Dash or similar), including web-based deployment of models and results.
Experience extracting, cleaning, and integrating data from different sources. Knowledge of key concepts around FAIR data and ontologies. Ability to query structured and unstructured data: SQL, Postgres, noSQL (MongoDB, Elastic Search) and knowledge of data I/O formats (JSON, XML)
Machine Learning: Supervised Learning: Linear & Logistic Regression, SVM, Random Forests, Neural Networks Unsupervised Learning: PCA, k-means Clustering; Statistics: Parameter Estimation, Hypothesis Testing, Model Validation; Probability Theory
Experience in extracting, integrating analyzing and visualizing biomedical data (ideally omics, genetics, imaging, or RWE)
Working knowledge of code development and reproducibility (Git, containers, Kubernetes)
Proactive and dynamic attitude with a demonstrable inquisitive mentality and a proven ability to formulate, articulate, and critically evaluate data driven hypotheses. Excellent teamwork skills and ability to work and thrive in cross disciplinary teams. High learning agility and a desire to be up to date with the latest computational and data technologies
Fluency in written and oral English with excellent presentation skills.
Nice to have:
Industry experience would be an asset.
AI/ML: practical experience with one major deep learning framework (PyTorch, TensorFlow).
Experience with Cloud computing and storage platforms (Azure, AWS, S3, Databricks)
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

You\\\'ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards

Commitment to Diversity and Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams\\\' representative of the patients and communities we serve.

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

Functional Area

Data Science

Division

Novartis Institutes for BioMedical Research

Business Unit

Diseases of Aging & Regen Medicine NIBR

Employment Type

Regular

Commitment to Diversity & Inclusion:

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Shift Work

No

Early Talent

Yes\\n \\n \\n \\n \\n \\n

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