The opportunity

The Data Scientist turns the huge amounts of data generated by payment transactions into unique insights that improve our measurement, monitoring and steering of merchant risk. He/she explores the opportunities that innovative machine learning, data mining and statistical analysis can bring to create value for merchant risk management. He/she collaborates with product teams, operations, data engineers and risk and compliance experts to plan, develop and deliver advanced analytics projects from start to finish, including all stages of project identification, stakeholder engagement, project management, and closeout.

Day-to-day responsibilities

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:

Risk Data Management & Project management

• In close collaboration with IT solutions & project teams, participate in the design, implementation and maintenance of the Risk Data Management solution that fully supports risk data aggregation capabilities, sound risk reporting & modelling practices and state-of-the-art data science capabilities!
• Participate in data management initiatives regarding risk data (data quality, data governance, etc.)

Methodologies & Risk analytics

• Conduct periodic stress test to identify factors that could potentially negatively impact the risk/reward of the portfolio and propose mitigation actions
• Design, implement and maintain advanced merchant risk predictive models

Reporting, Monitoring & Control

• Contribute to the development of merchant risk steering and portfolio view
• Automate and handle the merchant portfolio risk reporting covering credit risk, fraud risk, card scheme compliance risk and AML risk

Statistical methodologies and machine learning

• Works with models related to Risk scoring, stress testing
• Creates analyses for the purpose of portfolio segmentation and clustering
• Fits predictive modelling of future transaction flows and possible risky partners

Who are we looking for

We look for big thinkers. People who can drive positive change, step up and show what’s next – people with passion, can-do attitude and a hunger to learn and grow. In practice this means:

• Master of Sciences degree in a quantitative field (Statistics, Data Science, Quantitative marketing, Quantitative finance or similar)
• Good knowledge of predictive models and probability/statistics fundamentals such as linear and logistic regression
• Excellent knowledge of machine learning algorithms including classifiers, clustering algorithms, and anomaly detection
• Excellent understanding of relational model for database management and data modeling principles (conceptual/logical data models)
• Working knowledge of either R, Python or SAS for both data manipulation and statistical analysis
• Takes personal ownership, autonomous
• Result oriented and diligent with a strong ability to prioritize work in a fast paced and changing environment
• Learns continuously; seeks out knowledge, ideas and feedback
• Good communication skills for interacting effectively with both business and technical development teams !
• Fluent English
• Experience in the financial services industry a plus

Perks & Benefits

At Worldline you’ll get the chance to be at the heart of the global payments technology industry and shape how the world pays and gets paid. On top of that, you will also:

• Hybrid Working Policy
• Gift vouchers on the occasion of Christmas/Easter Holidays
• Private medical services
• 21 vacation days/year
• Referral bonuses for new hires recommended by you
• WFH & Flexible Working Hours
• Full access to the “Learning” platform