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Data Scientist Alternances Et Stages

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L'Oréal France
L'Oréal France

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Descriptif du poste

👀 What does it look like to work in data at L’Oréal?

Well, first it depends on your appetence! You could join either business-oriented projects (finance, marketing, supply chain…) or scientific-oriented projects in the R&I entity.

Let’s highlight the fact that positions at L’Oréal constantly evolve and adapt to our changing environment. But here is a sample of what you can do as a Data Scientist:

  • Deployment of the predictive model in a tool/application that could be easily use by everyone (e.g., prediction of future consumer trends) to improve the decision-making process
  • Continuous implementation and testing of different approaches, respecting the team’s principles in terms of code and methodologies
  • Perform code reviews on various projects, as well as present your code to your peers for continuous review and improvement
  • Exploratory analysis of a large database to extract insights from the data and work on the representation/visualization of results
  • Active communication of the results with the business/scientific stakeholders

Let’s be concrete:
For Reasearch & Innovation departments, you could work on:

  • Bayesian methods inventory (posterior probability; Bayesian power; Insurance; Bayes Factor; etc.)
  • Development of an application on R Shiny (R&I): Calculation of decision-making indicators, calculation of number of subjects, meta-analyzes
  • For Tech Accelerator (our incubator) , you could work on:
  • Construction of a similarity calculation engine between products on multiple parameters
  • Creation of a recommendation engine for our professional customers to simplify the purchase of multi-brand products.

And this is what you can imagine as take-away knowledge:
Learn from our data scientist experts!

  • Discover Data Science methodologies: Bayesian, NLP, Computer Vision
  • Apply Data Science to business and/or scientific projects with concrete added value
  • Ability to unite experts’ views and vulgarization of complex scientific results
  • Technical skills thanks to prediction algorithm and application development
  • Cross-functional work with business experts, scientific computing and data management from L’Oréal
  • Strengthen knowledge and manipulation of large-scale structured data

Profil recherché

Data science is a perfect match for you if:

  • Academic background: Master’s in data science, bio-statistic, statistics or applied mathematics
  • Understand business stakes and have a business-oriented appetence
  • You are curious and collaborative with a sense of popularization and argumentation
  • Have a good level of English

Here are some more technical requirements:

  • Python (unit test, docstrings documentation, object oriented…), SQL
  • Knowledge in statistic (tests theory, descriptive statistics, probability, integration, Bayesian analysis, mixt linear model)
  • R/R shiny programming
  • Technical and functional documentation skills

This could be a nice to have!

  • Back-end (flask, Django, NodeJS) and front-end (ReactJS, VueJS) skills
  • Used to Docker, Kubernetes, KubeFlow

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