Applied ML Scientist
Core
Building a customer intelligence layer that dynamically learns signals driving revenue outcomes and surfaces actionable insights to change business decisions.
Role type
Applied ML Scientist (IC)
Builds
Production ML pipelines and systems that ingest data, retrain models, and serve predictions at scale for revenue optimization.
Domain
SaaS / Customer Experience / Revenue Analytics
Deliverable
production ML models
Required skills
statistical modeling, machine learning, Python (production-grade), SQL, cloud data warehouses, LLMs/embeddings, experiment design, model monitoring
Preferred skills
causal inference, uplift modeling, orchestration tools (Airflow, dbt), AI-assisted development workflows
Technologies
Python, SQL, Snowflake, LLMs, embeddings
Responsibilities
Train, evaluate, and deploy models predicting revenue outcomes; design experiments linking customer signals to business results; build continuous learning ML pipelines; monitor model performance and drift; translate model outputs into actionable insights for stakeholders; partner with product/engineering to embed intelligence in user workflows.
Seniority
Mid-level (3-5 years), hands-on IC
