Data Science

Résumé du poste
CDI
Saint-Cloud
Salaire : Non spécifié
Télétravail non renseigné
Expérience : > 3 ans
Compétences & expertises
Contenu généré
Python
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Kyriba
Kyriba

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Le poste

Descriptif du poste

Kyriba is the global leader in cloud-based Enterprise Liquidity Management management solutions, delivering Software-as-a-Service (SaaS) financial technology to corporate CFOs and Treasurers. More than 2,600 global organizations (including Spotify, Ripple, Adecco, Auchan, Adobe, EuropCar, Eurostar International, Expedia, Electronic Arts, and Takeda) use Kyriba to enhance their global cash visibility, improve financial controls, and increase productivity across their cash and liquidity, payments, supply chain finance and risk management operations.

We are looking for an experienced Data Scientist to join our data science team. In this role, you will be at the heart of designing machine learning-based products.

 

Main Responsibilities:

  • Design and develop machine learning models

  • Collaborate with business teams and clients to identify potential improvements

  • Work with the ML Engineering team to deploy models to production

  • Present results and recommendations to stakeholders and customers

  • Participate in continuous improvement of data processes and methodologies

  • Contribute to the implementation and enhancement of MLOps practices

  • Technical Skills Required:

  • Proficiency in Python programming

  • Advanced experience with machine learning libraries

  • Expertise in time series forecasting

  • Knowledge of MLOps practices and associated tools

  • Soft Skills:

  • Excellent communication and technical explanation abilities

  • Strong team spirit

  • Ability to collaborate effectively with different departments

  • Intellectual curiosity and active technology watch

  • Autonomy and initiative-taking

  • Education and Experience:

  • Master's degree in Data Science, Applied Mathematics, Statistics, or related field

  • Minimum 3 years of professional experience in Data Science

  • Proven experience in deploying machine learning models to production

  • Why to join us:

  • Mentorship from experienced professionals in the area

  • Work in a collaborative, dynamic, and fast-paced environment.

  • Practical experience within an international SaaS provider leveraging public cloud solutions

  • Ongoing professional development and access to industry-leading tools and resources.

  • Networking opportunities within the organization

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