About
What you’ll do
Design and evolve graph data models for financial events, entities, and relationships (accounts, payments, invoices, trades, counterparties, ownership, etc.).
Translate business questions into graph queries and features (traversals, communities, centrality, paths, temporal patterns).
Build data pipelines for ingestion, cleaning, labeling, and feature engineering, including entity resolution and relationship extraction where needed.
Develop and validate statistical/ML models (risk scoring, anomaly detection, fraud patterns, forecasting, classification).
Create event-driven analytics using strong time semantics (event ordering, windows, causality assumptions, lifecycle states).
Partner with engineering to productionize models: batch + near-real-time scoring, monitoring, drift checks, and reproducible experiments.
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Languages
- English
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