Data Analyst
Data Analyst bij Rabobank in Utrecht, detachering, 36 uur/week, €90-105/uur, looptijd 13 maanden.
Warme-stoelsignaal: De startdatum ligt vóór de reactiedeadline en de reactietermijn is slechts twee dagen, wat samen sterk wijst op een reeds bekende kandidaat. Er is geen expliciete naam of interne ervaring genoemd, dus het blijft een onderbouwde indicatie.
Het taalmodel ziet aanwijzingen voor een zittende of vooraf gekozen kandidaat. Dit is een inschatting, geen bewijs. Zo werkt de warme stoel check.
Eisen
- Ability to uncover the real question behind a request and present recommendations convincingly
- Experience with PySpark, Databricks and Power BI
- Master’s degree in a technical field
- More than 7 years of experience in data analysis using Python
- Experience building end-to-end solutions using repositories, version control, pipelines and testing frameworks
- Experience guiding junior and mid-level colleagues and sharing your technical vision
Volledige omschrijving
Data Analyst bij Rabobank in Utrecht. Het betreft een detachering-functie voor 36 uur per week met een looptijd van 13 maanden. De salarisindicatie is €90,00 tot €105,00 per uur. Reageren kan tot vrijdag 25 september 2026, 09:00. As a Senior Insights Data Scientist you turn complex Transaction Monitoring data into actionable insights and production-ready solutions. You combine advanced analytics, software development and business knowledge to build automated solutions that help colleagues assess and optimise Transaction Monitoring rules and make better data-driven decisions.
Practical examples: Develop analytical models and decision logic to identify which customer segments, parameters or rules should be prioritised for tuning. Translate Above-the-Line and Below-the-Line tuning processes into data-driven recommendations and analytical solutions. Build production-ready dashboards and decision-support tools that make complex insights accessible to stakeholders.
Top responsibilities: Analytical pipelines: Build and improve pipelines that automate rule tuning and support scalable multi-parameter analysis.
End-to-end delivery: Deliver analytical projects from translating business questions to presenting clear recommendations to stakeholders.
Analytical products: Design and develop production-ready dashboards and analytical products for automated tuning and investigation workflows. Collaborate closely with stakeholders across Business, Technology and Operations to develop analytical capabilities that improve Transaction Monitoring efficiency and effectiveness.
You and your talent: Education: Master’s degree in a technical field.
Experience: More than 7 years of experience in data analysis using Python.
Technical skills: Experience with PySpark, Databricks and Power BI.
Engineering practices: Experience building end-to-end solutions using repositories, version control, pipelines and testing frameworks.
Communication: Ability to uncover the real question behind a request and present recommendations convincingly.
Leadership: Experience guiding junior and mid-level colleagues and sharing your technical vision.
Facts: Working time: 36 hours per week.
Data scope: Transaction data from more than 9.5 million customers is analysed.
Eisen: Master’s degree in a technical field; More than 7 years of experience in data analysis using Python; Experience with PySpark, Databricks and Power BI; Experience building end-to-end solutions using repositories, version control, pipelines and testing frameworks.
Competenties: The ability to uncover the real question behind a request and present your recommendations convincingly; Experience guiding junior and mid-level colleagues and sharing your technical vision.
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