Data Scientist

COMO is building the future of cyber resilience. Our AI-native platform helps organizations understand their ability to recover from cyberattacks, identify critical gaps and dependencies, and prepare for what happens after an attack.

We're looking for a Data Scientist to solve one of the hardest problems in our product: grouping thousands of cloud assets into the applications they actually belong to, and ranking which ones matter most.

• Build the application-classification engine: combine graph structure, tags, naming, and network signals into application groupings with confidence scores.
• Build asset-criticality classification: rank what matters by production-ness, blast radius, and usage.
• Own measurement: define how we know our models and our product are good.
• Design the feedback loop: turn customer corrections and manual overrides into training signal.
• Keep an eye on cost: design models and pipelines that stay efficient as data volume grows.
• Ship models into the product via API or pipeline.

• M.Sc. or higher in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• 4+ years of experience in a Data Science or ML role, with at least one production system doing entity resolution, clustering, or classification.
• Strong research and statistics foundations: experiment design, evaluation methodology.
• Experience defining and owning quality metrics for a model or product.
• Experience shipping models into a product (API or pipeline).
• Strong feature engineering over graph and relational signals, comfortable with both embeddings and classic ML.
• Strong SQL and Python data-stack skills, with cloud-native experience.
• Understanding of cost optimization for data and ML workloads at scale - advantage.
• Experience with infrastructure or operational data - advantage.
• Security, observability, or IT-asset domain background - advantage.

Python, Polars, PostgreSQL, Kafka, AWS Bedrock, with an AI-native workflow throughout.