HBP (Amsterdam - Haarlerbergpark), Netherlands
Onsite
Amsterdam | 36-40 hours
At ING, we believe that every customer deserves support that fits their situation. Within Collections, our ambition is to help customers regain financial control through personalised, data-driven interventions that improve both customer outcomes and business performance.
As a Data Scientist within BRAIN, you will play a key role in shaping this future. You will develop advanced analytics, machine learning, and AI solutions that help us better understand customer behaviour, make smarter decisions, and deliver more effective support at scale.
This is not a traditional Data Scientist role. We are looking for someone who combines expertise in Collections with strong technical capabilities. In this role, you will work closely with experienced colleagues to turn business challenges into practical data science solutions that can be used in production. You enjoy working at the intersection of business and technology and want to create measurable impact for customers through data and AI.
BRAIN is a team of Data Scientists within the Collections domain. Our mission is to use data, advanced analytics, and AI to improve customer outcomes, optimise operations, and support better decision-making throughout the Collections journey.
We develop and maintain solutions such as customer segmentation models, behavioural models, Next Best Action engines, smart routing algorithms, forecasting models and Generative AI applications. Our work directly contributes to a more personalised, proactive, and effective approach to helping customers with financial difficulties.
You will work closely with Data Analysts, Customer Journey Experts, Engineers and Operations colleagues in multidisciplinary Agile teams. Together, we bring analytical solutions from concept to production and continuously measure their impact.
The team is based in Amsterdam and works in a hybrid setup.
As a Data Scientist, you contribute to the development and implementation of analytical solutions that create measurable customer and business value.
You will:
Develop machine learning, optimisation and AI solutions that support Collections decision-making.
Design and improve customer segmentation, behavioural and predictive models.
Contribute to recommendation systems and decision engines that drive personalised customer interactions.
Contribute to translating business challenges into scalable analytical solutions.
Analyse large and complex datasets to uncover actionable insights and opportunities.
Collaborate with Engineers to deploy, maintain and improve production-ready solutions.
Apply MLOps in day-to-day development, including model deployment, monitoring and lifecycle management.
Use Google Cloud Platform to develop and operationalise data science solutions.
Work with Azure DevOps and Azure Pipelines to enable CI/CD and automated deployment processes.
Monitor model performance and continuously improve analytical solutions based on business impact and customer outcomes.
Communicate insights, recommendations and model outcomes to both technical and non-technical stakeholders.
We hire smart people like you for your potential. Our biggest expectation is that you'll stay curious. Keep learning. Take responsibility. In return, we'll support you in becoming an even more awesome version of yourself.
As a Data Scientist, you combine domain expertise with strong technical capabilities. You understand how Collections works and know how to create value through analytics.
You bring:
Demonstrated experience in Collections customer journeys and treatment strategies.
Experience working with Collections data, including data quality, feature engineering and analytical data management.
Knowledge of credit risk and customer behaviour within financial services.
Strong programming skills in Python and SQL, preferably BigQuery and Oracle.
Experience developing maintainable, production-oriented code using object-oriented programming principles.
Experience with Azure DevOps, Azure Pipelines and CI/CD practices.
Experience working with Google Cloud Platform in a data science or machine learning environment.
Familiarity with Vertex AI pipelines.
Understanding of MLOps, model deployment, model monitoring and model lifecycle management.
Understanding of machine learning, predictive modelling and statistical techniques.
Understanding of customer segmentation, behavioural modelling and optimisation techniques.
Good communication skills in Dutch and English.
A master’s degree in Data Science, Statistics, Econometrics, Mathematics, Computer Science or a related field, or 3+ years of experience in Data Science.
It is a plus if you have experience with:
Designing, executing and evaluating experiments such as A/B tests.
Generative AI, Large Language Models, decision engines, recommendation systems or reinforcement learning.
Responsible AI, model governance, privacy requirements and regulatory considerations within financial services.
We want to make sure that it’s possible for you to strike the right balance between your career and your private life. Find out more about our employment conditions.
The benefits of working with us at ING include:
A salary tailored to your qualities and experience
25-28 vacation days depending on contract
13th month salary
8% holiday payment
Pension scheme
Hybrid working
Personal growth opportunities
An informal working environment with innovative colleagues
Curious about how ING empowers people and businesses to move forward?
Discover what we do and what we can offer you.
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