The Data Scientist will work alongside quantitative scientists, domain experts and product developers to ensure teams succeed in answering scientific questions using the data42 platform. They will help our users to apply and develop analytical methods and predictive models that deliver impact on research and drug development programs. Furthermore, they will collaborate on analytical pipelines (e.g. for imaging or genomics) that can be re-used across the platform. Within the project and when working with our users, data42 data scientists will develop and advocate for good data science practices. data42 Data Scientists will also contribute to the design of our platform, to make it accessible, useful and an appealing toolset for the whole data science and AI community.
#data42 #DataScientist #ComputationalBiology
Our customer, a pharmaceutical company based in Basel, needs reinforcement. For a temporary employment (asap until 14.10.2022; 1 year), we are looking for a
Data Scientist – Biostatistician (m/f/d), 100% (temporary)
- Computational biology and statistical genetics
- Applied/computational data science and large-scale / ‘big data’ computation
- Statistical and machine learning / deep learning
- Analysis of Clinical trial datasets (SDTM/ADAM) and/or RWE data
- Ensure that scientific teams are enabled and supported to achieve their goals at data42
- Contributes to the acceleration of data science through activities such as the development of reusable pipelines for the data preparation and analyses
- 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 machine learning, deep learning, data visualization and structured/unstructured data analytics towards the scientific goals of their team.
- Acts as an advocate for good data science practice across data42
- The Data Scientist plays a role in knowledge sharing across data42 and wider data science community at NVS, contributing their insights and research to ensure that we understand state of the art approaches, and can apply them where appropriate
- PhD in a quantitative / computational science (e.g. bioinformatics, machine learning, statistics, physics, mathematics, …),
- Fluent in English (oral and written)
- Strong experience with Python for data analysis (scikit-learn, numpy, …),
- Experience with R for data analysis (tidyverse, mlr, …),
- Reproducible data science (notebooks, git/versioning …).
Desirable additional skills in two or more of the following areas:
- 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 or images.
- Bioinformatics (around DNA / RNA / proteomics data analysis) and/or statistical genetics
… please contact Mr. Renato Imboden by phone on 061 269 90 60