Fonction professionnelle: Digital

Type de poste: Permanent

Type de contrat: Full - Time

Site: Paris

Pays: France

“Our ambition is to make L’Oréal a Beauty Tech Company “ says our CDO Lubomira ROCHET.  L’Oréal is in a period of growth in digital and is building a dynamic and multidisplinary teams from different backgrounds to deliver on our exciting mission to accelerate our digital transformation.


L’Oréal, leader in beauty tech operates globally to deliver entirely new concepts that surprise and delight our consumers, and drive our business. We are investing in services that are “augmenting” our consumers experiences with our products (Make Up Genius, connected brush, UV patch etc) and we are building an ecosystem for beauty tech through open innovation.

Are you willing to be part of this exciting adventure? Join us! 


As a data scientist specialized in machine learning and deep learning, you will join our AI team at the heart of Global Digital Organization. The role of the team is to support our businesses by delivering high added-value, end-to-end AI applications. Use cases range from marketing optimization to operational excellence with a strong focus on making the way we do business more data driven. To be noticed: as a beauty company, we love working with images, so you should expect to get your hands dirty with Convnets and GANs! Also, leveraging the vast amount of text data available (reviews, comments, transcripts of videos…), you’ll have to use the latest innovations in NLP.  



MAIN MISSIONS
- Develop, rigorously test and implement artificial intelligence models in response to our objectives with regards of real-world constraints

- Identify opportunities where data science can help improve or transform the way we do businessFind, extract, retrieve, organize and structure data, coming from heterogeneous sources

- Design and organize large-scale data annotation exercises (e.g. MTurk)

- Build POCs & MVPs and carry them to production

- Leverage the latest open source research to keep our models at the edge of performance

- Promote AI within the company by successfully building models and applying them to business issues

- Communicate with business teams in order to contribute to digital transformation and data-driven mindset



PROFILE

- At least 1-3 years of experience in the field of Machine Learning or related

- You have a Master Degree or PhD in one of the following fields: machine learning, computer science, statistics, probability, optimization, linear algebra

- You have a hands-on experience with machine learning, and deep learning in particular (CNN, RNN,, LSTM, Auto-Encoder, GAN, etc..). Experience in Reinforcement Learning is a plus (Deep Q-Learning, Bandits algorithms...)

- You can manage to expose and deploy your work using DevOps tools (e.g. Jenkins, containers and HTTP services)

- You enjoy reading research papers, technical blogs and trying new AI algorithms

- You have good communication skills and understand where AI could benefit to the company



REQUIRED SKILLS

- Good knowledge of Python, and bonus points if you have experience with one of the following languages : Julia, R, C++, Java.

- Experience with data science and machine learning frameworks (numpy, opencv, pandas, scikit-learn...) and with at least one of the main Deep Learning frameworks.

- Ability to work with Git and Linux (including basic shell commands)

- You can deal with various sources of data (images, videos, text, CSV files, NoSQL and SQL databases), including noisy ones.

- You can easily combine mathematical modelling and software development.

- You have redeveloped and/or improved standard models.

- You have an entrepreneurial spirit and drive your projects to their completion.

- You can manage priorities.

- Your English is excellent

- You can present and explain your work to business stakeholders and non-technical audiences



WHO ARE YOU?

- An enthusiastic, curious, creative person, who is always on the lookout for new technologies and methodologies;

- You are a builder;

- You like bringing your ideas face to face with a challenging environment and test them in practice; 

- You want to develop and enrich your expertise through teamwork.



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