Python Job: Data Scientist Transaction Monitoring

As a Data Scientist Transaction Monitoring you can have societal impact, by catching the criminals using analytics models to analyze Rabobank transactions of 8+ million customers.

You and your job
Preventing Money Laundering & Terrorist Financing are one of the key aspects for our society and our organisation, and as a bank we play a major role in this field. In order to be effective in fighting financial crime, we need smart individuals like yourself who get their energy from looking into data, patterns and behaviour of our customers in order to uncover illegal activities. Together with the team you will be responsible for optimizing our current Transaction Monitoring (TM) system and eventually (not on short term) for introducing more advanced analytics methodologies such as Machine Learning into our TM models.

As you can imagine, doing this job requires statistical, investigative and operational expertise and if done successfully, will make sure that our analysts are able to focus on the true positive alerts – hence spend their time on truly value-adding activities. In summary, in this role you will be on the front line of fighting financial crime.

Practical Examples

As a Data Scientist TM you will:

• Identify model improvements and provide statistically significant proof to justify implementation

• Present your results and think together with the stakeholders how to improve which alternative analyses to perform

• Translate regulatory and procedural requirements around tuning (and back-testing) into a methodology and way of working that fits Rabobank

Facts & Figures

• 36 hours per week
• 20+ other data scientists to collaborate with and learn from within the same team
• 40+ other roles to collaborate with and learn from within the same team (e.g., Anti Money Laundering Experts, Developers, Product Owners, Scrum Masters and more)
• 43,822 Rabobank colleagues around the world

• Carry responsibility for (parts of) the data science model(s) in one of the key areas within Tribe KYC Tech
• Build transaction monitoring detection rules
• Function as counterpart for stakeholders in the team (non-data scientists) and outside the team

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. So we are very curious about what you can bring to our team in the Tribe KYC Tech.

“Our team combines expertise in fighting financial crime with the power of data to build a robust, efficient detection system. As data scientists we are responsible for building and optimizing the models used to detect criminal behaviour. This is a growing, dynamic team perfect for any data scientists looking for opportunities for learning and creativity.”

Iona, Data Scientist Transaction Monitoring

The 60+ people in our Transaction Monitoring team are responsible for detecting money laundering and terrorism financing risks, using analytics models. Working together is the way we work; as 1 multi-disciplinary, highly talented and motivated team at Rabobank. Talking of Rabobank: We are a Dutch bank that operates in 38 countries for over 9,5000,000 customers. Together with these customers, our members and partners we stand side by side to create a world in which everyone has access to enough healthy food. In the Netherlands we work to create a country in which people are happy with how they live, work and do business.

You and your talent

• Academic degree (MSc / Phd) in Data Science, Mathematics or a related field
• 2+ years’ experience in advanced analytics / modelling / artificial intelligence activities (ideally with large data sets) working with Python (PySpark, Spark and Azure Databricks experience is a plus)
• Excellent verbal and written communication skills in English
• Motivation to catch criminals by making our TM system more effective; in other words, you are motivated to build models that realize measurable impact for the bank, not necessarily to build the most complex advanced analytics model.

• Structured, precise, communicative, and can work well with different people and roles
• Thrive in a high-impact, dynamic and high-paced environment
• Be pro-active, have a business focus and can-do mentality to make the difference in fighting financial crime