Description:

Gewenste startdatum: zsm
Einddatum: 18 december 2026
Voertaal: Engels
Kennis van de Nederlandse taal is niet vereist.
Vaste kantoordagen op maandag en donderdag
Kandidaten moeten in Nederland woonachtig zijn
Geen ZZP

Goed om te weten: het betreft een gecombineerde functie. De kandidaat zal zowel data scientist als software engineering werkzaamheden uit gaan voeren.

As a Data Scientist / Software engineer, you can have social impact by detecting criminal behaviour and simplifying business processes using graph analytics patterns by analysing Rabobank transactions of 8+ million customers.

You will work in a team focused on enriching the enterprise knowledge graph (Neo4j) using entity matching. The team is responsible for entity matching across a range of use cases, developing and refining models to accurately identify and link related entities.

You help the team in turning their innovative power and experiments into high quality production ready products, by bringing a lot of coding experience.

Practical examples

• Build responsible and cost effective Graph solutions for millions of customers.

• Analyse and optimize critical code to improve performance and scalability

• Turn some explorational notebooks into a maintainable codebase

Top responsibilities

• Create re-usable building blocks, which can be used all over the bank.

• You bring experience on solving complex technical challenges and elevating the skills of those around them.

• You take the lead in sharing best practices, mentoring teammates and fostering a culture of engineering excellence

Requirements:

• You have a Bachelor or Master degree in Data Science, Applied Mathematics, IT or a related field

• You have at least 5 or more years of experience working as a Data Scientist with strong focus on software engineering

• You have strong object-oriented programming and software engineering skills, Fast API and Python knowledge is a must

• You are skilled in Git, Databricks and Pyspark.

• You have a passion for building and bringing to production clean, well-structured, maintainable and testable solutions.

• You have experience in making components that can be re-used and standardized to support scale

• You are curious by heart, open to learning, proactive and experienced in collaboration with colleagues.

• You communicate well in the English language (both spoken and written).

• Basic understanding of statistical modelling and machine learning.

• Experience with cloud platforms, preferably Azure

• Experience in model deployment, performance tuning, and monitoring leveraging MLOps/DevOps is a plus.