Senior Data Scientist

Job Description

REQUIREMENTS

• Strong applied statistics and machine learning background with experience deploying models in production.
• Advanced production Python skills, including writing tested, maintainable code in a shared codebase.
• Hands-on experience with Kafka and streaming or event-driven systems.
• Hands-on experience with graph databases such as Memgraph or Neo4j.
• Working knowledge of networking fundamentals and telemetry protocols (SNMP, syslog, OpenTelemetry).
• Experience with entity resolution, record linkage, or deduplication techniques applied to messy data.
• Experience building monitoring and evaluation systems for production models (confidence calibration, drift detection).

Preferred

• Experience with MLOps tooling for model versioning, deployment automation, or CI/CD pipelines.
• Familiarity with providing structured context to LLMs for reasoning over topology or troubleshooting.
• Experience with anomaly detection or forecasting applied to operational monitoring data.
• Background in cybersecurity, network detection and response, or infrastructure observability.

RESPONSIBILITIES

• Design, build, and ship models for entity resolution and deduplication directly into production pipelines.
• Own the full lifecycle of models in production, including deployment, monitoring, retraining triggers, and incident response.
• Build and maintain model-serving and evaluation infrastructure, including precision/recall tracking and drift detection.
• Write production-grade Python code and work within streaming and graph-based systems like Kafka and Memgraph.
• Analyze network and telemetry protocol data (syslog, SNMP, OpenTelemetry) to transform raw signals into structured model inputs.
• Partner with security, alerting, and observability teams to apply modeling to anomaly detection and telemetry pattern recognition.
• Mentor other data scientists on best practices for model development and reliable production operations.

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