Offers “Sanofi”

Expires soon Sanofi

Data Scientist

  • Internship
  • Cambridge (Cambridgeshire)
  • IT development

Job description



Job Overview:

Advanced Analytics - Data Scientist will execute advanced computational approaches to accelerate and optimize evidence-based pharmaceutical product development.  He/She will leverage high-dimensional population health data to support R&D, Medical, HEVA, commercial product development, access and business strategy. The Advanced Analytics Data Scientist roles will generate analytics required by healthcare decision makers to support patient access and use of Sanofi medicines and he/she will contribute to the insights required by Sanofi internal teams to develop and commercialize the most impactful medicines.  

Job Responsibilities:

·  Get to apply a broad array of capabilities spanning 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 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.
·  Design and implement data models, perform statistical analysis and create predictive analysis models
·  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 Health Services research, Medical Economics, Medical Informatics, Biostatistics, or Computer Science, computer engineering or related field 
·  Relevant Masters Degree, with at least 3 years of relevant industry experience
·  Experience with open source technologies, ML libraries, and programming languages (R, python)
·  Experience with advanced ML techniques (neural networks/deep learning, reinforcement learning, SVM, PCA, etc.).
·  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)

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

Sanofi Glassdoor: #GD-SA

Sanofi LinkedIn:

At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.

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