Our Data scientists opportunities - Apprenticeships

Key Skills

Python Programming, Django, Node.js, SQL, API integration, Bayesian networks, Linear regression, Kubernetes-K8s, R Programming, Statistics, Kubeflow, Flask, R-Shiny, Probability

Job Description

[APPRENTICESHIP]

*** From September 2022 ***

*** Starting September 2022 ***

Join our teams !!!

We have many apprenticeships positions to fill in Data Science this year in L'Oréal Global Beauty Tech !

Our mission: offering you an amazing, personalized experience inside our tech entity. A real kick-start for your career!

Didn’t imagine L’Oreal as an amazing Tech Company? Wait a minute! 

L’Oréal is present in 130 countries on five continents. For more than a century, L’Oréal has devoted itself solely to one business: create beauty that moves the world; it is now the industry world leader with €29 billion consolidated sales.

Today, L’Oréal includes 1900 tech positions and it’s constantly growing. Especially with our ambition to become the #1 BeautyTech company, meaning inventing the beauty of the future while becoming the company of the future.

To achieve this ambition, L’Oréal needs to continue recruiting many diverse, innovative, skilled and passionate minds in different tech domains such as Data, Digital, Cloud, Cyber Security, IT Architecture, DevOps, Applications and Infrastructure.

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

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

You want to know more? Take a look at this:

Joining L'Oréal means joining a company that:

1. Invests in Tech and positions its Tech teams at the heart of its transformation strategy.
2. Allows its employees to have a real impact, to test their ideas, to innovate and to build our future.
3. Has a powerful and innovative HR policy with a very dynamic accompanying along your internship
4. An amazing community of intern and alumni
5. Has chosen to uphold strong values and to be particularly advanced from a social and environmental point of view (strong diversity and inclusion policy, L'Oréal for the Future program, commitment to numerous communities, etc.).