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Dreem // neurotechnology
 
Engineering, Internship    Paris, le-de-France, France    Posted: Friday, October 11, 2019
 
   
 
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JOB DETAILS
 

Dreem has a unique relation to analytics. As a member of the Dreem analytics team, youll have the opportunity to work in close relation with nearly all other teams (Product, Marketing, Engineering, Science, Finance).

Dreems path & product are unique & to stay successful we rely heavily on data to guide both strategic & day-to-day decisions. Dreem & its users generate large quantities of very diverse data which needs careful & creative analysis to provide these crucial insights. By joining our team youll be able to guide decisions, create & implement tools, discover & learn faster than in any other company, all of it fighting one of the most challenging health issue of present times.

As a Data Analyst intern, youll have the (rare) opportunity to work on all layers of the analytics stack: preparing & processing data (Data engineering/BI), analyzing data (Data analysis / Data science) & sharing your results with stakeholders (dashboards / presentations / reports).

Since we deal with very varied topics & teams, be prepared to learn a lot on countless topics & dive head-first into complexity. Also, youll be able to work on both very rapid projects with instantaneous impact, & longer & deeper explorations & analysis projects.

The Analytics team was created as we sold our very first headbands. Because Dreem is so new, closely understanding our users needs & usage has always been a strategic activity. Since its creation, the team has provided insights, tools & training to ensure everyone in the company can leverage data to improve his work.

In addition to passive analytics where one looks at normal activity, we also drive many active initiatives where we take a more experimentalist approach. Over the years weve setup several specialized systems to include our users in product development through large-scale remote tests or targeted feedback collection.

Missions

  • Analysis of large & complex datasets to provide relevant & timely insights
  • Contributing to analytics data-ingestion / transformation / processing pipelines
  • Conducting exploratory analysis
  • Share your findings as dashboards, presentation & reports
 
 
 
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