The opportunity

📍Partner with Compliance operations, Product, Engineering and other stakeholders to build descriptive and predictive models to identify anomalous activity 📍Maintain, update, and enhance the transaction monitoring and customer risk scoring codebases 📍Ensure that all activities meet model validation and audit requirements. 📍Design and build proof-of-concept models to test hypotheses and help with idea generation and refinement 📍Develop unsupervised and supervised models to find anomalous and risky activity 📍Use structured and unstructured data to enrich transaction monitoring and customer risk scoring metadata 📍Develop anomaly detection, data quality checks, and data modeling tools to monitor key performance indicators to improve the efficiency of models

Skills you should HODL

📍5+ years of industry experience in data science 📍Data science experience in the financial industry 📍A consistent track record of performing data analysis using Python and SQL 📍Experience using statistics and machine learning to solve complex business problems 📍Versatility and willingness to learn new technologies on the job 📍The ability to clearly communicate complex results to technical and non-technical audiences 📍Experience with containerization and deployments (docker, kubernetes) 📍Experience with CI/CD (Gitlab, Argo, Airflow) 📍Familiarity with financial crime and market abuse typologies is a plus 📍Experience with crypto/blockchains preferred