Data Scientist

Princeton, New Jersey
Industry: Biotech / Pharma
Job Number: JN -022021-60287

We are looking for a Data Scientist with a translational bioinformatics background for late stage oncology studies. Strong statistical modeling and analysis experience wanted. They will analyze the molecular profiles of diseases, so Translational or Precision medicine experience is also wanted. Candidate should be able to speak Cox model, logistical regression, random effect, mixed effected models and Time-varying covariates. They should know when to use each model. Strong R and machine learning/AI skills.

 

Responsibilities

  • Under the guidance of senior analysts, define and execute biomarker data analysis plan for late-stage oncology trials and other datasets
  • Perform analysis of clinical and biomarker datasets (e.g., large-scale omics datasets including RNASeq, Exome and Whole Genome Sequencing, single cell sequencing) and derive clinically meaningful interpretations
  • Identify potential biomarkers for patient enrichment strategies and gain mechanistic insights of responses and resistances to treatments
  • Summarize analysis results and write analysis report
  • Evaluate and adapt latest scientific findings and methods into bioinformatics analysis plans.

Qualifications:

  • Ph.D. in bioinformatics, statistics, biological, or related fields. Experiences in biotech or pharmaceutical industries is a plus
  • Strong experience using R for complex data analysis is required. Experiences with other high-level programming language such as Python is a plus.
  • Experiences with reproducible research practices, including GitHub, is required
  • Experiences working with clinical study data is required; familiar with late stage clinical development process is a strong plus
  • Expertise in application of modern machine-learning/AI approaches is a plus
  • Deep understanding of disease biology in oncology is a strong plus
  • Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects while conforming with rigorous requirements of clinical studies
  • Broad experience with data generated by one or more high-throughput molecular assays: next-generation sequencing, flow cytometry, mass spectrometry proteomics, etc.
  • Strong problem-solving and collaboration skills, and rigorous and creative thinking
  • Excellent communication, data presentation, and visualization skills.
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