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Data Scientist (Biostatistician) 100%

Job description

Data Scientist (Biostatistician)


The Data Scientist will work alongside quantitative scientists, domain experts and product developers to ensure teams succeed in answering scientific questions using the data 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, data scientists will develop and advocate for good data science practices. 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.


We are looking for data scientist bringing expertise in two or more of the following areas:


  • 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


Additional information:

Ideal start date: asap

Duration: 12 month contract

Extension: possible

Work location: Basel

Workload: 100%

Responsibilities:

  • Ensure that scientific teams are enabled and supported to achieve their goals
  • 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


The Data Scientist plays a role in knowledge sharing across data science community, contributing their insights and research to ensure that we understand state of the art approaches, and can apply them where appropriate.


Your profile:

  • Education (minimum/desirable): PhD in a quantitative / computational science (e.g. bioinformatics, machine learning, statistics, physics, mathematics)
  • Languages: 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)

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