Data Scientist

Job Summary We are seeking a Data Scientist to model and analyze financial events and entity relationships using graph-based data. This role involves designing graph schemas, building analytical pipelines, and delivering insights such as risk detection, anomaly detection, and event-driven intelligence. The ideal candidate will have strong expertise in graph analytics, machine learning, and financial data modeling. Key Responsibilities Design and evolve graph data models for financial entities and relationships Translate business problems into graph queries, features, and analytical models Build data pipelines for ingestion, cleaning, labeling, and feature engineering Perform entity resolution and relationship extraction Develop machine learning models for risk scoring, anomaly detection, and forecasting Implement event-driven analytics using temporal data modeling Collaborate with engineering teams to productionize models and monitor performance Communicate insights through dashboards, reports, and documentation Required Qualifications Bachelors degree in Data Science, Computer Science, Statistics, or a related field, or equivalent practical experience Strong foundation in statistics and machine learning concepts Experience with graph databases and graph modeling concepts Proficiency in Python (e.g., pandas, NumPy, scikit-learn) Experience with SQL and data engineering practices (ETL, data quality, versioning) Knowledge of graph query languages such as Cypher, Gremlin, or SPARQL Strong communication and stakeholder management skills Preferred Qualifications Experience in financial data modeling (payments, trades, reconciliation, etc.) Familiarity with graph algorithms (PageRank, centrality, clustering, etc.) Experience with entity resolution and identity graph techniques Experience with NLP for event extraction Familiarity with cloud platforms (AWS/Google Cloud Platform), orchestration tools, and model deployment Knowledge of REA (ResourcesEventsAgents) modeling Education: Bachelors Degree