Data Engineer

1 week ago

Singapore VUI SYSTEMS PTE. LTD. Full time

Responsibilites Explore the data landscape: profile on-chain, off-chain, fiat and KYC datasets to understand structures, gaps and lineage. Prototype features for ML & rules: translate typologies and investigator hypotheses into measurable candidate variables (e.g., velocity, counterparty risk scores, graph metrics) using SQL/Python and big data. Validate data quality & drift: run one-off QC checks, anomaly detection and basic stratified sampling to confirm a feature's stability before production hand-off. Collaborate with modelers & investigators: iterate quickly on feature definitions, and refine logic based on model performance and investigative feedback. Maintain a living feature catalogue: version each prototype, capture business meaning, lineage and sample metrics so production data engineers can industrialize it. Support regulatory look-backs & ad-hoc research: replay historical data, craft quick queries and surface insights that help Compliance and Compliance Product teams respond to audits or enforcement actions. Stay current: monitor emerging AML data-science techniques (graph ML, LLM embeddings, anomaly detection) and assess their applicability to crypto and fiat monitoring. Requirements: 4+ years in data engineering / analytics with hands-on feature-engineering and exploratory data analysis; AML or broader compliance experience is a plus. Expertise in SQL and Python (Pandas, PySpark, or similar) within notebook workflows, plus hands-on experience with big data stacks such as Spark/Hadoop, Databricks and Alibaba DataWorks Working experience in banking domain Solid grounding in machine-learning fundamentals (supervised, unsupervised, evaluation metrics) and how features impact model performance. Experience translating AML / regulatory concepts into quantitative features-e.g., structuring, layering, sanctions exposure. Ability to work collaboratively in a fast-paced, dynamic environment. Optional skills: Working knowledge of the crypto ecosystem, VASP regulations, and typical AML data flows (KYT, KYC, TM, case management). Qualifications: Bachelor's degree in Computer Science, Engineering, or related field; Master's preferred. Minimum 5 years of experience in a similar role.

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