This is what we offer you
Gross monthly salary between € 3.516 and € 5.021 (scale 07).

Thirteenth month's salary and 8% holiday allowance
10% Employee Benefit Budget
EUR 1,400 development budget per year
Hybrid working: balance between home and office work (possible for most roles)
A pension, for which you can set the maximum amount of your personal contribution

View all our benefits.

Job Title

Junior Data Scientist

Job Description
Data Scientist External Fraud - Data & Analytics Early Career Program

Ready to turn data into action and help stop fraud before it happens? Grow your skills during this Early Career Program at Rabobank.

You & your role

As Data Scientist External Fraud, you know the secrets of turning complex data into valuable insights that help protect customers, society and Rabobank from fraud. You help analyse millions of transactions and client interactions, identify suspicious patterns, and contribute to solutions that prevent financial crime. Together with your colleagues, you make a direct impact by helping customers keep their money safe.

In addition to your role, you will spend part of your time on personal development activities, training and learning opportunities within the Data & Analytics Early Career Program.

In short

Assessing and developing action plans for new fraud modus operandi.
Applying Artificial Intelligence and Machine Learning to improve fraud detection and prevention.
Participating in business challenges and development activities within the Data & Analytics Early Career Program.

You and your future

During this Data & Analytics Early Career Program at Rabobank, you will develop your career over 18 months by becoming an expert in Data Science within the External Fraud area. You will remain part of one team, receive technical training, work with a buddy, and be supported by a business mentor. Together, we help you build the skills and confidence to succeed.

And then? After completing the program, you will continue working within your team as a Data Scientist. You will have built a strong professional network, strengthened your technical expertise, and further developed your personal and professional skills.

Practical

Length: Data & Analytics Early Career Program: 18 months.
After which you will continue to work with us as Data Scientist External Fraud.
Hours per week: 40.
Salary: €4007,80.

Your growth in the Data Analytics Early Career Program

At Rabobank, we believe real growth comes from doing. From celebrating successes and learning from the moments that could have gone differently. That is why we offer you the perfect balance between freedom and guidance.

The Data Analytics Early Career Program is all about your development. You will intentionally invest in discovering who you are, what drives you, and how you want to grow as a professional. You will be challenged to step outside your comfort zone and explore where your strengths truly lie, sometimes in places you did not expect yourself. Through these experiences, you will learn where you can make the greatest impact.

And you will not do it alone. Every Friday, we come together at the office with the Data Analytics community. In an open and informal environment, we share knowledge, experiences, insights, and learn with and from each other.

From day one, you will build a strong and valuable network that will benefit you throughout your career. Throughout the entire programme, you can count on intensive support from experienced colleagues. Whether you want to specialise in a specific field or explore what energises you most, your growth always comes first.

Learning from each other

Development is our top priority. Because the best way to learn is by doing, through mistakes and successes. At Rabobank we offer you the right balance between freedom and supervision. To develop talents you never thought you possessed. To specialise in a professional field or explore the things you are good at and enjoy doing. During your Data Analytics Early Career Program you can count on us for excellent supervision. You will work with experienced colleagues and have lots of contact with young professionals.

Work on your own development & shape the world around you

For us, your development and that of society go hand in hand. That is why we want to invest in you and work together towards a better world. We summarise this in one sentence: "At Rabobank, you work on yourself and the world around you at the same time."

This is reflected in your personal development budget, our hybrid work environment and a healthy balance between work and private life. You can contribute to solutions for our clients, while also helping Rabobank address societal challenges and fulfil our mission: Growing a better world together.

We believe everyone should feel welcome, valued and able to be themselves. Diversity, equity and inclusion are important parts of our culture, because different perspectives help us make better decisions and create more impact.

You and your talent

Master's degree or PhD in Econometrics, Mathematics, Physics, Data Science, Industrial Engineering or another STEM-related field.
0-2 years of work experience.
Experience with at least one programming language such as Python, R or Java.
Knowledge of statistics and data modelling.
Strong analytical skills and a strategic mindset.
Able to make complex topics understandable for different stakeholders.

You and the job application process

We believe in the power of difference. Bringing together people's differences is what makes us an even better bank. What can you bring to Rabobank? We cannot wait to hear from you.

So get in touch straightaway (and certainly before the closing date on Sunday 2nd of July 23:59).

Interviews will be held via MS Teams or at our offices in Utrecht.
Assessments are part of the application process.
We look forward to meeting you in person during the selection days.
If you are selected for an interview, Bo, our virtual assistant, will reach out to you via SMS and email to schedule the interview.
A security check is part of the process.
We respect your privacy.

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