Computational Statistician - Oncology

Roche

Basel, Switzerland
Not specified
Phd in biostatistics or bioinformatics
Proficiency in r and python programming
Experience with high-dimensional molecular data
Roche is seeking a Computational Statistician in Oncology to join their Translational Oncology sub-unit within the Computational Biology department. The ideal candidate will possess a PhD in a quantitative field, experience with high-dimensional molecular datasets, and strong skills in statistical methods, predictive modeling, and machine learning

Job Summary

  • The role involves executing data and analytics strategies to develop a competitive advantage for Roche's Pharma Research and Early Development organization.
  • Candidates will collaborate with world-leading computational scientists to apply computational biology specifically within the Oncology space.
  • The position requires fostering a culture of continuous improvement, challenger safety, and inclusive teamwork to deliver high-value insights for patients.

Matching Summary

Match Score: 85

Roche is seeking a Computational Statistician in Oncology to join their Translational Oncology sub-unit within the Computational Biology department. The ideal candidate will possess a PhD in a quantitative field, experience with high-dimensional molecular datasets, and strong skills in statistical methods, predictive modeling, and machine learning.

Skills & Requirements

Must-have

  • PhD in Biostatistics or Bioinformatics
  • Proficiency in R and Python programming
  • Experience with high-dimensional molecular data
  • Knowledge of Linux/Unix and HPC environments
  • Strong understanding of disease biology

Nice-to-have

  • Prior pharmaceutical industry experience
  • Familiarity with CDISC clinical data standards
  • Matrix leadership capabilities
  • Expertise in population statistical genetics
  • Integrative multi-omics data analysis skills

Key Requirements

  • PhD in Biostatistics, Bioinformatics, or related quantitative field
  • Proven experience with genomics and transcriptomics datasets
  • Demonstrable technical expertise in AI/ML applications
  • Ability to lead multidisciplinary teams without formal authority
  • Strong foundational understanding of Oncology disease biology

Work Rights

Not specified

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