Lead Data Scientist

at  Worldline

Job Description
Lead Data Scientist
Bucharest, Romania

Your project work will address four key priorities in the development of our analytical capabilities:

• Data engineering: in close collaboration with Worldline’s BI team who has the responsibility of developing and maintaining data management platforms, you will develop a risk data repository for the analysis of millions of electronic payments that are processed daily by Worldline
• Reporting and Data Sharing: you will create reports and data sharing solutions using BI tools to help risk teams get access to the data that they need to best perform their tasks. Moreover, you will collaborate with users in refining the design of informative dashboards and data sharing systems.
• Merchant portfolio optimization: you will contribute to develop a risk-based pricing approach to achieve an optimal risk/reward balance consistent with the company’s business strategy
• Machine learning and platform building: you will contribute to building machine learning models and putting them in production, building platforms and making sure the models function properly within the environment

In your role, you will explore the opportunities that statistical analysis and data engineering can bring to create value for the management of merchant risk.

Your project work will address four key priorities in the development of our analytical capabilities:

• Data engineering: in close collaboration with Worldline’s BI team who has the responsibility of developing and maintaining data management platforms, you will develop a risk data repository for the analysis of millions of electronic payments that are processed daily by Worldline
• Reporting and Data Sharing: you will create reports and data sharing solutions using BI tools to help risk teams get access to the data that they need to best perform their tasks. Moreover, you will collaborate with users in refining the design of informative dashboards and data sharing systems.
• Merchant portfolio optimization: you will contribute to develop a risk-based pricing approach to achieve an optimal risk/reward balance consistent with the company’s business strategy
• Machine learning and platform building: you will contribute to building machine learning models and putting them in production, building platforms and making sure the models function properly within the environment.

Depending on your main area of specialization, and our team’s business needs, you may be required to place more focus on one or another of our key priorities, at the end of your internship based on the results you will be considered for either a data scientist or a data engineer position.