About the role
Use your AI and machine learning skills to combat financial crime. At Deloitte.
- Execution of data analysis and development of (machine learning) models to detect irregularities in large transaction streams, in collaboration with our clients.
- Set up and manage reliable data processing pipelines (ETL) so data is processed efficiently and securely.
- Apply GenAI to speed up analyses, for example to support feature engineering.
- Visualize model results and translate them into concrete recommendations for clients on combating financial crime.
- Report to your manager, colleagues and clients.
- Work in a fast-growing team with plenty of opportunities for personal development.
Our team advises clients on preventing and detecting financial crime. Our Financial Crime Analysts use (machine learning) data models and GenAI to make this possible.
Naturally you want to discover and learn new things every day and you have the confidence to trust your own judgement. But most importantly, be the true you. The one and only you. With your personal strengths, view of the world and unique personality. You need the following qualifications for the position of Analyst Financial Crime Technology:
- A recently completed, quantitatively oriented Master’s degree, such as AI, business analytics, mathematics, computer science, econometrics or a related field.
- A good mix of statistical skills and an affinity with IT systems, financial crime and financial business processes.
- Experience with programming (knowledge of SQL or Python is an advantage).
- Excellent proficiency in Dutch and English; both verbally and written.
Do you want to help fight financial crime, but using cutting-edge technology instead of manual checks? As an Analyst Financial Crime Technology you develop and deploy data processing pipelines and (machine learning) data models that automatically analyze millions of bank transactions and flag irregularities. You make model insights understandable for our clients’ management, delivering direct impact on risk management and the prevention of financial crime.
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