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STATISTICIAN - DATA SCIENTIST - INTERNSHIP

CONTEXT

The resource will work in a team of mathematical/statistical experts to drive the application of advanced and state-of-the-art statistical principles in Technical Research & Development (TRD). The candidate will be part of Global Data Analytics and Innovation (GDA&I) which is a newborn, international and dynamic team which is driving data analytics and digital innovation inside TRD department following a continuously growing number of projects in many different fields. GDA&I group supports TRD projects for statistical analyses (i.e. multivariate data analysis, etc.) and enhances innovation through the application of chemometrics and machine learning algorithms. 

PROJECT DESCRIPTION

The candidate will work side by side with expert statisticians/data scientists on improvement of data collection and management to enable quick and reliable analyses. In addition, he/she will contribute to perform statistical data analyses in partnership with TRD functions, document, report and communicate results in the form of technical documents and presentations.    

COMPETENCIES

The intern will develop competencies related to non-clinical statistical methodology and multivariate data analysis applied to vaccines drug substance and drug product processes as well as fluency with the most common statistical tools and programming languages used in pharma industry. Beside that, the resource will take familiarity with vaccines development principles.

REQUIREMENTS:

  • University Master’s degree in Statistics, Mathematics, Engineering or related field

  • Fluent English required

  • Good knowledge of Excel

  • Good knowledge of at least one between R or SAS (Python is a plus)

  • Ability to deliver clear communications and foster excellent working relationships with peers and management

  • Good team player – works well in cross-functional and multi-cultural teams

  • Analytical mind, good attention to detail and problem-solving


SEDE: 
Siena, Italia


Degrees of interest: University Master’s degree in Statistics, Mathematics, Engineering or related field