Data Scientist
Core
Build and deploy anomaly detection ML models that run unattended on tens of thousands of time series to separate good data from bad in an agentic data management platform.
Role type
Senior IC machine-learning engineer (time series anomaly detection)
Builds
Production anomaly detection models, data profiling, SQL generation, and lineage parsing for enterprise analytics and AI pipelines.
Domain
Data management, time series analysis, unsupervised learning
Deliverable
production ML models
Required skills
ML model deployment, statistical modelling, Python, SQL (advanced), performance optimization, algorithm prototyping
Preferred skills
Time series analysis, signal processing, inference engineering, Rust
Technologies
Python, Rust, SQL, Postgres, Redis, Kubernetes, Helm, Claude, Gemini, Codex
Responsibilities
Build algorithmic core including anomaly detection and change point detection; take methods from research papers to production models; tune models to reduce over-alerting on cyclical metrics; evaluate model improvements without labelled data; maintain validator metrics in SQL across multiple warehouses; collaborate with Customer Success and Support on data quality issues.
