IA Engineer at Natixis Investment Managers Operating Services

Hybrid - Paris

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At NIM-OS, you will join the Data Science & BI team, which is made up of professionals who are passionate about artificial intelligence and data processing. In this team, we work to develop innovative data science solutions, integrate machine learning models into our processes and explore new methodologies to optimize our strategic projects. On a day-to-day basis, your mission is to:

  • Participate in the design and implementation of solutions for complex problems;
  • Manipulate and process data from different sources to make it actionable;
  • Collaborate with other teams (data engineers, developers, architects, etc.) to integrate data science solutions into existing processes;
  • Communicate technical results clearly to non-technical audiences;
  • Research and explore new methodologies and technologies in data science. This position is based in Paris with the opportunity to work remotely. You also have the opportunity to commit yourself to society and causes that are close to your heart through our corporate foundation. You work in a hybrid, inclusive and collaborative working environment.

Requirements

Education

  • Higher education

Experience

  • First experience (internships or alternance) in the field of data science and BI

Skills

  • Programming languages such as Python, R or Scala
  • Machine learning frameworks
  • SQL and NoSQL database management systems
  • Data visualization tools such as Power BI or Python libraries
  • Teamwork and sharing ideas clearly and convincingly
  • Rigorous and organized with attention to detail

Languages

  • English (C1)

Responsibilities

  • Participate in the design and implementation of solutions for complex problems
  • Manipulate and process data from different sources to make it actionable
  • Collaborate with other teams (data engineers, developers, architects, etc.) to integrate data science solutions into existing processes
  • Communicate technical results clearly to non-technical audiences
  • Research and explore new methodologies and technologies in data science

Technologies

PythonRScalaMachine learning frameworksSQLNoSQLPower BIPython libraries

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