Data Scientist, Scientific Data Analysis

Job description

Job Description

The Informatics department (NX) at Novartis Institutes for BioMedical Research (NIBR) is looking for an independent Data Scientist to join the multidisciplinary Scientific Data Analysis team that brings together bench scientists, software engineers, statisticians and bioinformaticians to provide high quality analyses of large scale experimental data.

Work location will be Basel, Switzerland.

You will be responsible for the exploration and development of deep neural network approaches for applications in drug discovery. You will work closely with drug discovery teams and computational biology colleagues to frame key questions, define data sets for these efforts, and perform machine learning and analysis aspects of these projects. Furthermore, you will identify tractable machine learning problems in all stages of drug discovery from disease biology discovery, to target identification, assay development, safety, and patient stratification.

Specific activities include:
• Understanding relevant datasets, both those generated internally and those from the public domain
• Providing guidance on study design to project teams
• Applying machine learning algorithms – especially deep learning methods when applicable – to drug discovery problems
• Educating colleagues about machine learning approaches
• Communicating data analysis results and methods to the NIBR community and the broader scientific community
• Staying current with new developments in machine learning methodology

Desired profile

• PhD or Master's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering or a related field
• Several years of experience in data science or data analysis; industry experience preferred
• Proven experience in applying deep learning approaches
• Expertise in machine learning
• Expertise in data analysis and statistics
• Experience working in Unix/Linux environment
• Strong scientific curiosity and initiative; work experience in life sciences preferred
• Demonstrated ability to work collaboratively as part of a team
• Strong analytical skills and proven capability to provide clear, correct, and actionable results
• Excellent interpersonal and communication skills
• Fluency in English (oral/written)