Géén ZZP!

Background information
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.

You will be responsible for optimizing our current Transaction Monitoring (TM) system and ensuring it is future proof for introducing more advanced analytics methodologies such as Machine Learning into our TM models.
Our TM system evaluates millions of transactions every single day and needs to perform withing the boundaries that have been set with respect to computing time and resources. Our model is in ongoing development and new (computationally intensive) functionality is being added. Your responsibility would be to optimize performance of model components. The challenge is that this is not solely a technical assignment. Working in the context of transaction monitoring requires you to thoroughly understand the functionality of the model and its components.

The candidate will collaborate in the team to help contribute to delivering the following results:
• Build functionality into our data model (TDM) while continuing to combine all (30+) data sources required for Transaction Monitoring in an computationally efficient way. Our sources
contain event data [e.g., transaction data and logging data from sources like CNA, AZS, PEX, RASS] and enrichment data (e.g., customer data and cash data from sources like Siebel,
Omnikassa, Geldmaat, VCM)]
• Ensure model component design enables Rabobank to comply with all regulatory, audit and other internal requirements
• Set-up the model components to function as solid building block that can function on its own, and can be leveraged by other (KYC/TM) projects as well
• Ensure the computational performance of the Transaction Monitoring solution is sufficient for daily batch scoring and for one-off runs on multiple years of data (using (Py) Spark)

Our ideal candidate:
• Is motivated to work on models that realize measurable impact (i.e. catch criminals), not necessarily to build the most complex advanced analytics models
• Is structured, precise, communicative, and can work well with different people and roles
• Thrives in a high-impact, dynamic and high-paced environment
• Is pro-active, has a business focus and can-do mentality to make the difference in fighting financial crime

For this position we require:
• Academic degree (MSc / Phd) in Data Science, Computer Science, Mathematics or a related field (required)
• Software development skills such as Git, bash scripting and release management and proven success in bringing analytics models to production (required)
• A minimum of 5 years of experience in advanced analytics / modelling / artificial intelligence activities working with large data sets (required)
• Excellent verbal and written communication skills in English (required)
• Highly skilled in working with Python, PySpark and Spark (required).

Nice to have
• Skilled in working withing Azure Databricks (preferred)