Shape the future of ARaymond as part of our global Digital Lab Community. You’ll join a team at the beating heart of our company’s daily transformation. And you’ll feel valued for what you bring both as a person and professional, thanks to our servant-leadership model that puts your voice and wellbeing first.

You will be involved in the ARaymond transformation….. With your professional background and your energy, you will actively participate in all the activities to maintain and improve the ARaymond Digital environment, you will be in charge to provide data driven insight to solve use cases relying on industrial operations and customer data. You will help build data engineering assets and statistical/machine learning models to surface actionable business insights. The scientist will also work with data analysis systems and modelling environments (Data Robot, Dataiku, Azure ML, AWS Sagemaker …).

• Data extraction and structuring 
  • Identify valuable data sources and automate collection processes 
  • Undertake preprocessing of structured and unstructured data
  • Analyze large amounts of information to discover trends and patterns
• Development of artificial intelligence algorithms    
  • Build predictive models and machine-learning algorithms
  • Combine models through ensemble modelling
  • Present information using data visualization techniques
• Active participation in projects 
  • Propose solutions and strategies to business challenges
  • Collaborate with engineering and product development teams
  • Provide data science expertise to project
• Work closely with IT data team (data engineers, devops…)
• Technology watch on data science tools
   

• Excellent statistical, machine learning and data mining skills
• ML in more specific terms: Clustering, Time series, Regression, Decision trees, Deep Learning (CNN/RNN/GNN) and NLP.
• Experience working with relevant technical tools, platform and systems such as Python, R, SQL, Jupiter Notebook, Power BI …
• Good knowledge of python/R Libraries ( Scikit learn, pandas, numpy, tensorflow, keras, pytorch…)
• Experience in Analytics with time spent on driving and implementing Analytics insights
• Proven ability to create PoCs of Advanced Analytics solutions
• Experience maneuvering ETLs
• Efficient Data Cleaning techniques
• Familiarity with data visualization in R, Python, or JavaScript
• Experience in data engineering using Spark / Hadoop is a plus
• Experience in model/data drift and lifecycle (mlflow) is a plus
• Experience in ai model fairness / interpretability (Shap, Lime) is a plus.
• Experience using / building APIs is a plus (Flask…)
• Must have skills on data modelling and data architecture
• Must have good written and verbal communication skills with both technical and executive-level clients. 
• Must have strong decision-making capabilities
• Must be result-oriented with expert problem solving and analytical skills 
• Must have good business understanding
• Fluent in English written and spoken