Data Science Intern

Kyriba is the world leader in proactive cash management. Their mission is to enable CFOs to be more agile and efficient in managing their cash flow and liquidity. Its SaaS Treasury and Risk solutions enable clients to optimize their cash flow, manage their risks and manage their capital.

Kyriba was established in 2000 and has more than 700 employees, serving more than
2,000 customers worldwide. Kyriba, headquartered in San Diego, also has offices in New York, Paris, London, Tokyo, Singapore, Hong Kong, Rio de Janeiro and Shanghai.

In March 2019, Kyriba raised $ 160 million to intensify innovation and accelerate the growth of its platform.

Kyriba empowers CFOs, Treasurers, and their IT counterparts to transform treasury, payments, working capital, and connectivity solutions to activate liquidity as a dynamic, real-time vehicle for growth and value creation. Kyriba is a secure, scalable SaaS platform that leverages artificial intelligence, automates payments workflows, and enables thousands of multinational corporations and banks to maximize growth, protect against loss from fraud and financial risk, and reduce operational costs. With 2,000 clients worldwide, including 25% of Fortune 500 and Eurostoxx 50 companies, Kyriba manages more than 1.3 billion bank transactions per year, and 250 million payments for a total value of $15 Trillion annually. Kyriba is headquartered in San Diego, with offices in Dubai, Frankfurt, London, Paris, Shanghai, Singapore, Tokyo, Warsaw and other major locations. For more information, visit www.kyriba.com.

Role: 

The goal of this internship is to use deep learning to analyze changes in the Kyriba source code. The objective is to :

- detect problems in the code before they are noticed in production

- select the tests (unit tests, regression tests) to be performed

- predict root cause in case of test failure

The candidate will review the state of the art and implement language models (fine tuning, full training) applied to the software engineering.

The intern will be supported by a team of data scientists already working on the subject, as well as data engineers.

Source: https://github.com/saltudelft/ml4se

Profile:

Student in the last year of engineering school or master's degree in data science, statistics, mathematics or applied mathematics

Deep learning knowledge

Solid knowledge of Python

Effective communication skills in English

Ability to work in a team

Curiosity