Data Scientist

Sanofi Aventis   •  

Cambridge, MA

Industry: Pharmaceuticals & Biotech

  •  

Less than 5 years

Posted 186 days ago

Job Responsibilities:

  • Apply a broad array of analytics skills including machine learning, statistics, text-mining/NLP, and modeling to extract insights to structured and unstructured healthcare data sources, pre-clinical, clinical trial and complementary real-world & digital information streams.
  • Work on a variety of team-based projects providing expertise in analytical and computational approaches. 
  • Work with the latest tools and technologies to impact drug development 
  • Contribute to the Advanced Analytics plans for projects across R&D, Medical Affairs, HEVA and Market Access Strategies and Plans.
  • Leverage analytics involving large datasets to refine and improve data models.
  • Build and construct prototypes of Advanced Analytic work-flows.

Essential Skills & Experience:

  • PhD or ScD in quantitative field such as Medical Informatics, Mathematics, Biostatistics, or Computer Science, Engineering or related field 
  • Relevant Master’s Degree, with at least 2 years of relevant industry experience (level II), or Master’s degree with relevant Essential Skills and Experience (level I).  Candidates with a Bachelor’s degree with at least 3 years in a relevant discipline and commensurate analytics experience will be considered.
  • Experience with open source technologies, ML libraries, and programming languages (R, python)
  • An ability to interact with a variety of large-scale data structures e.g. HDFS, SQL, noSQL
  • Experience working across multiple compute environments to create workflows and pipelines (e.g. HPC, cloud, linux systems)
  • Experience with any of the following: biomedical data types/population health data/real world data/novel data streams.
  • Strong oral and written communication skills
  • A demonstrated ability to work and collaborate in a team environment

Desirable Skills & Experience

  • Experience with reproducible and collaborative technology platforms (e.g. github, containers, jupyter notebooks)
  • Experience with big data analytics platforms and/or workflow tools
  • Exposure to NLP technologies and analyses
  • Knowledge of some datavis technologies (ggplot2, shiny, plotly, d3, Tableau or Spotfire)

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