Financial Crime Analytics (Data Scientist)
For our client who is a leading global analytical services provider focused on advanced research and analytical services for the world's best financial institutions, including leading investment banks and asset management companies, we are looking for a Financial Crime Analytics (Data Scientist).
- Develop, maintain, and enhance quantitative models associated with our anomalous market activity detection and monitoring platform
- Create tools to allow analysts to understand alerted activity in-depth
- Refine business requirements and develop programming specifications
- Work in partnership with stakeholders to develop and drive initiatives that transform and modernize the capabilities and services of monitoring within the compliance function
- Assess current and future state of surveillance, platform, policies, and procedures to promote continuous improvement
- Min. 2 years data analysis/model development experience using R, Python / PySpark
- Very strong experience in application development using technologies like Python, Spark, Hadoop, GitHub, Hdfs
- Hands-on experience in data mining/analytics
- Experience in Big Data products like Cassandra, Cloudera.
- Programming experience using SQL/Oracle/Sybase/Hive or any relational databases/Big Data
- Strong knowledge of AML transaction monitoring with at least 2 years of relevant experience in financial crime analytics (additional exposure to customer segmentation, scenario testing, and validation)
- Rich experience in threshold tuning & optimization is a must.
- Well-versed with threshold tuning methodologies & implementation. Exposure to ATL/BTL
- Knowledge of AML or fraud analytics with at least 2-3 years of relevant experience in financial crime analytics
- M.S. in Statistics, Computer Science or a related quantitative discipline
- Excellent verbal and written English communication skills