Graph Data Scientist
Tasks
- Apply graph algorithms for pattern and relationship discovery
- Build fraud detection models rules and investigative use cases
- Conduct entity resolution identity matching and relationship mapping
- Create visualizations link charts and dashboards
- Design graph based analytics solutions for fraud detection
- Develop data pipelines graph schemas and graph data models
- Develop graph models for entities and transactions
- Document methodologies and model findings
- Evaluate model performance and recommend improvements
- Integrate graph analytics with machine learning and statistical analysis
Perks/Benefits
- Comprehensive health coverage
- Federal holidays off
- Flexible PTO
- Professional development support
- Remote work
- Tuition reimbursement
- Wellness stipends
Skills/Tech-stack
Anomaly Detection | Centrality | Classification | Clustering | Community Detection | Cypher | Data Pipelines | Entity Resolution | Feature Engineering | Graph Algorithms | Graph Databases | Graph Embeddings | Graph Knowledge | Graph Knowledge Graphs | Graph analytics | Identity matching | Knowledge graphs | Link Analysis | Machine Learning | Model Validation | Neo4j | Network Analysis | Path analysis | Predictive Modeling | Python | Risk scoring | Statistical Analysis
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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