Data engineer with data analytics experience

 We are looking for you, if you:

• have experience with Python especially with pandas, sklearn, pyspark, numpy,
• are familiar with statistical inference (e.g., predictive analytics, clustering, Machine Learning Algorithms),
• have knowledge of Apache Spark,
• can manage accesses, data, and code repository (code review and testing on Azure DevOps),
• are proficient in data visualization and  you have some experience in reporting,
• have excellent communication skills, including being able to explain technical terms to non-technical audience,
• have organizations skills, being able to decompose big tasks, plan, prioritize and estimate required time for own work.

You'll get extra points for: ​ 

• financial knowledge about transaction analysis,
• experience of applying data analysis and data science in financial sector.

Your responsibilities:

• performing data driven based analysis of the specific client behaviors related to the Transaction Monitoring (TM) Risk typologies,
• determine the relevance and significance for ING’s clients and products. The resulting unusual and higher-risk behavior specifications are input for the business rules, applied in TM for the detection of this behaviors – expected to use for analysis machine learning methods applied in Spark and Python.  

Information about the squad:

Transaction Monitoring (TM) analyzes customer transactions for signs of financial crimes. TM Optimization focuses on improving the efficiency and effectiveness of the automated monitoring solution by reducing noise while maintaining effectiveness and identifying financial crime risk.

As the Data Engineer in TM Optimization Analytics, you will be supporting Optimization activities to ensure optimal configuration of TM global monitoring systems.

The role naming convention in the global ING job architecture will be “Engineer III”