Publicis Groupe, is the world’s third largest communications group.  Publicis Global Media Operations (PGMO), is a Groupe wide practice driving transformation across Publicis solution hubs through a connected global network, proprietary technology, and consistent and scalable best in-class processes; empowering global marketing and digital business transformation. 

We are looking for a Research Scientist that will define the novelle protocols/algorithms/models to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models of Deep Learning and Machine Learning to test the effectiveness of different courses of action.

They must have strong experience using a variety of machine learning methods, using a variety of processing tools, building and implementing models, using/creating algorithms and creating/running simulations. They should be familiar with the whole workflow of machine learning to deliver the successful and useful models.

They must have a proven ability to drive business results with their data-based insights and be comfortable interacting with a wide range of stakeholders and functional teams to have a global view of the business demand. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Scope of work

Key tasks

• Communicate and understand the business demand behind the mathematic modelling
• Analyse data from company databases to drive optimization and improvement for product development, and marketing techniques
• Assess the effectiveness and accuracy of new data sources and data gathering techniques including feature engineering.
• Based on the business demand and available data, propose the best technical solutions
• Develop custom DL, ML and non-ML models and algorithms of multiple domains from NLP to Data prediction
• Define the evaluation approach of models
• Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Keeping abreast of developments in corresponding domains

Requirements:

Key skills

• Master degree from Computer science, Mathematics, Statistics and other relative disciplines
• 4+ years of experience in machine learning and deep learning
• Experience using computer languages (Python, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of a variety of machine learning techniques (Bayesian statistical modelling, clustering, decision trees, boosting, artificial neural networks, etc.)
• Knowledge of popular DL and ML libraries: Tensorflow, Torch, Keras, Sklearn, Scipy, Xgboost, Huggingface…
• Knowledge of popular cloud infrastructure: Google Cloud, AWS, Microsoft Azure, …
• Excellent written and verbal communication skills for coordinating across teams.
• Experience in code management using Git

Optional skills

• Experience in Ecommerce or Advertising verticals is a plus
• Experience on NLP, Time Series Forecasting, Computer vision, and other relative domains is a plus
• Experience on popular NLP and Computer vision libraries is a plus: Spacy, NLTK, OpenCV, …
• Experience on parallel computing and GPU acceleration is a plus
• Experience on data engineering

Nice to have:

• Publications in top academic conferences and journals in the related domains
• The good rank in competition in ML and Data competitions
• Regular contributor in open-source ML libraries

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.