It's fun to work in a company where people truly BELIEVE in what they're doing!
 

We're committed to bringing passion and customer focus to the business.

Kyriba is a global leader in liquidity performance that empowers CFOs, Treasurers and IT leaders to connect, protect, forecast and optimize their liquidity. As a secure and scalable SaaS solution, Kyriba brings intelligence and financial automation that enables companies and banks of all sizes to improve their financial performance and increase operational efficiency. Kyriba’s real-time data and AI-empowered tools empower its 3,000 customers worldwide to quantify exposures, project cash and liquidity, and take action to protect balance sheets, income statements and cash flows. Kyriba manages more than 3.5 billion bank transactions and $15 trillion in payments annually and gives customers complete visibility and actionability, so they can optimize and fully harness liquidity across the enterprise and outperform their business strategy. For more information, visit www.kyriba.com.

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