Data scientist (F/M/D) - Paris

  • Paris, France
  • Full-time

Company Description

At EcoVadis, we envision a global marketplace where sustainability intelligence influences every business decision – improving economies, people's lives and the planet we all depend on. EcoVadis counts industry leaders like Johnson & Johnson, L’Oréal, Nestlé, and Michelin, among the 80,000+ businesses on its network. 

With an ambitious, purposeful mission to provide the world's most trusted business sustainability ratings, EcoVadis is driven by a diverse team sharing the core values of commitment, customer-focus, courage, integrity, kindness and happiness. EcoVadis offers you exciting career opportunities in an innovative and dynamic environment. We are looking for passionate team players from a variety of disciplines – from CSR and sustainability experts to customer engagement and engineering talents – to join us to make a real impact on the environmental and social practices of companies worldwide. Join us! 

Job Description

We are looking for a highly motivated Data Scientist to join our growing R&D Team, responsible for using machine learning to drive innovation across the organization. 

Your global responsibilities will include (but will not be limited to):

  • Leverage data to solve business problems.

  • Uncover trends, patterns, correlations and other relationships in data and deliver actionable business insights from this information by creating algorithms and advanced analytic models using statistical, data mining and / or machine learning tools and techniques.

  • Build and maintain data-driven optimization models, experiments, forecasting algorithms, and machine learning models.

  • Benchmark your model against the current ones.

  • Leverage tools like R, Python, Azure & SQL to drive efficient analytics.

Qualifications

You must have an outgoing personality along with an exceptional level of drive and a desire to pursue a career in an international and dynamic environment. You should have excellent verbal and written communication, critical thinking and analysis. 

 

  • Master’s degree in quantitative discipline(Statistics/Applied Math, Data Science, Applied Linguistics and Text Analytics, Computer Science) 

  • 2+ years of overall experience in Machine Learning/NLP and data mining techniques

  • Excellent understanding of Machine Learning techniques and algorithms, such as Decision trees, word embeddings, neural networks

  • Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling. Use effective text representations to transform natural language into useful features. 

  • Eager to learn attitude for logical problem-solving skills.

  • Enthusiastic, can-do attitude who can work independently as well as contribute to the team.

  • Strong communication skills both within and outside teams.

  • Demonstrable software engineering experience from previous work experience, coding competitions, or publications preferably in Python.

  • Any experience with Azure or other cloud provider would be a distinct advantage.

Skills, abilities and work standards:

  • Continuous Learner – Ability to continually develop and improve one’s skill and knowledge to perform effectively and adapt to change in the workplace. Development occurs through a variety of learning opportunities, seeking feedback, and individual reflection. 
  • Personally Effective - Making use of all of the personal resources at your disposal (talents, skills, energy, and time) to achieve goals. 

  • Authentic - Being honest and authentic in communication, feedback and strategy.

  • Results-driven - Setting high goals for themselves and others. They accomplish their goals by effectively working through challenges and demonstrate commitment to the company's goals. 

  • Creative Problem Solver - Focused on improving their practices and results. They are open to new ideas and they maximize available resources. 

  • Collaborator & Partner - Works effectively with others to achieve shared goals through cooperation, sharing knowledge, joint problem-solving, and celebrating success. 

 

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