Medior Data Scientist Customer Due Dilligence (CDD) - Machine Learning

As a Medior Data Scientist, you play a key role in preventing financial and economic crime by continuously improving our Customer Due Diligence (CDD) models. You develop and optimise advanced analytics models, set up automatic monitoring for existing models, collect and discuss insights with relevant stakeholders and thereby continuously improve the detection of risks in customer portfolios. You join an area of 17 multidisciplinary squads and become part of a squad of ambitious and driven professionals.

This is what we offer you

• Salary: Gross monthly salary between EUR 4,516 and EUR 6,449 (scale 09) for a 36-hour work week.
• Extras: a thirteenth month, 8% holiday allowance, and a 10% Employee Benefit Budget.
• Development budget: EUR 1,400 development budget per year for your growth and development.
• Hybrid working: a balance between home and office work (possible for most roles).
• Pension: decide for yourself the amount of your personal contribution.

Examples from practice

• Work on the development of our CDD ML model, including data collection, design, testing, and implementation, in alignment with IT, Architecture, and Business.
• Deliver quarterly and yearly monitoring reports to stakeholders, analysing model performance and identifying improvement opportunities.
• Improve the current way of working, supporting junior colleagues in adopting best practices and ensuring consistency across the team.

Facts & figures

• The CDD RNL Detection area is organised in 17 multidisciplinary squads.
• 9.5 million customers worldwide

Top 3 responsibilities

• Develop new CDD models to detect risky customers by using a mix of techniques, balancing model effectiveness and explainability.
• Timely and accurately report on model performance, and discuss findings with relevant stakeholders to determine where most effort should be placed to develop more advanced models.
• Determine new approaches to detect risky customers, challenger models, and proof of concepts to always be one step ahead in fighting economic crime.

Together we achieve more than alone. We believe in the power of difference. Bringing together people's differences is what makes us an even better bank. We are very curious about what you can bring to our team at the Tribe FEC Tech.

You will be part of the Customer Due Diligence Retail NL Detection team. The 100+ people in our Customer Due Diligence team are responsible for detecting risks in our customer portfolio using analytics models. Collaboration is our approach; as one data-minded team within Rabobank, we combine our expertise to create a safer financial environment.

Work on yourself and the world around you at the same time

For us, your development and that of society go hand in hand. That is why we want to invest in you and work together for a better world. At Rabobank, you work on yourself and the world around you at the same time. You will see this reflected in your personal development budget, our hybrid working environment, and a healthy balance between work and home. You can work on banking services for our private and business customers, as well as societal issues such as food and energy transitions.

You & your talent

• Academic degree (MSc / PhD) in Data Science, Econometrics, Mathematics, Engineering (or equivalent).
• 5+ years of experience in advanced analytics and machine learning modeling, ideally with large data sets. Proficiency in Python, PySpark, and Spark is essential. Experience with Azure Databricks is a plus.
• Thrive in a high-impact, dynamic and high-paced environment (experience with Agile working is a plus).
• Excellent verbal and communication skills in English.
• Pro-active, customer-centric and can-do mentality to make difference in fighting economic crime.
• Excellent communication skills, with the ability to convey technical concepts to non-technical stakeholders effectively.
• To be considered for this position you must be located in the Netherlands, re-location is not possible for this role.

Questions about the role: Jaspreet Singh, Analytics Lead CDD via jaspreet.singh@rabobank.nl