Summary
We are looking for a data scientist bringing expertise in two or more of the following areas:
• Analysis of omics data of various modalities
• Experience with data from Immunology.
• Applied/computational data science and large-scale / ‘big data’ computation,
• Development and management of disease area focused data pools
• Biostatistics for the analysis of clinical data (SDTM/ADAM) and/or RWE data
• Machine learning / deep learning and large language models
About the Role
Your responsibilities will include, but are not limited to:
- Ensure that scientific teams are enabled and supported to achieve their goals at data42.
- Programmatically (using python or R), identifying and filtering scientifically relevant cohorts of patient data often from very large (20-50k+) individual patient datasets using a range of project specific criteria e.g. age, gender, geography, lab biomarkers, disease states, treatment drugs etc.
- Develops frameworks for generation and reporting of key results, quality benchmarks for data, models, and impact in collaboration with our data scientist users.
- Applies their expertise in biostatistical analysis, machine learning, data visualization and structured/unstructured data analytics towards the scientific goals of their team.
- Contributes to the acceleration of data science through activities such as the development of reusable pipelines for the data preparation and analyses.
- Acts as an advocate for good data science practice across data42.
Minimum Requirements:
- Preferably Ph.D. in scientific or relevant discipline or equivalent.
- At least 2 years of professional experience in the pharmaceutical sector
- Experience with biostatistics in one or more therapeutic areas (strongly preferred clinical data in combination with other data modalities like DNA / RNA / proteomics for multi-modal data analysis)
- Strong experience with R or python for data analysis and statistical modelling specifically for patient level clinical data
- Experience in using machine learning models to predict clinical endpoints using multimodal data.
- Experience with use of AI/GenAI/LLMs for automating or accelerating data- or data science related processes.
- Experience with the principles and tools of good data science practice (e.g. git/versioning).
- Excellent communication and stakeholder management skills
Desirable additional skills in two or more of the following areas:
- Knowledge of CDISC data standard (SDTM, ADaM)
- Experience with pooling of clinical trial data
- Understanding of the drug discovery and development process
- Experience working in the field of Immunology and / or Cardiovascular, Renal, Metabolism (CRM)
- Experience with computational environments for large-scale data science (e.g. high-performance computing or Spark),
- Statistical and machine learning, and / or applied deep learning methods for time series data.
- Experience in using the Foundry platform for data analysis.
- Strongly encouraging candidates with prior biostatistics or other data analytics experience in a pharmaceutical company, in clinical trial environment with clear demonstration of one or more relevant therapeutic area understanding and demonstrated aspirations by either already pursuing a data science role or intending to transition to a data science focused role
Why Novartis: 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
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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: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network