qualification-
1. Minimum of 3-5 years of professional experience with data science/ predictive modelling.
2. Relevant Master degree.
3. Excellent programming skills (Python).
4. Hands-on experience with big data tools (Hadoop, Spark, Cloudera).
5. Pre: experience with Network Science, Neo4j or Cypher language.
6. Excellent communication skills in English, both verbally and written.
7. Open and curious, both analytical and creative.
8. You know how to translate complex concepts into easy to understand.
As a Senior Data Engineer Network Analytics you will:
– Remodel data into a graph data model, engineer network features, and build graph models;
– Analyze data from various sources, query graph databases, run (graph) algorithms like PageRank and
community detection on a large scale and create visualizations;
– Collaborate with AML experts and other graph data Engineers to find new opportunities where network
analytics is beneficial for risk detection techniques;
– Perform data analyses using Python
and PySpark;
– Work with large data sets (as you can imagine, years of historic transaction data does not fit in an excel
file).
You will be part of the Network Analytics D&A squad and use data to improve customer experiences,
create insights, reduce risks and costs and help to keep our financial system safe.
We do this by developing prediction models, creating and improving existing algorithms, applying
advanced analytics to create insights using complex data and actively research new techniques.
The team has a dynamic, and entrepreneurial culture with a lot of room for developing new expertise and
experimenting with innovative ways of working.
Tagged as: data engineer, pyspark
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