Data Scientist II, ML Infrastructure

Tech Stack

Responsibilities

• Translate research-grade DS workflows into production ML pipelines using Airflow, WandB, and Ray.
• Apply and productionize causal inference methods using the production ML stack (propensity scoring, IPW, TMLE).
• Partner with ML engineers and product teams to identify opportunities for improved tooling, metrics, and measurement methods.
• Leverage rich metadata and engagement signals to build data-driven frameworks that improve platform efficiency.
• Design and build centralized ML platform tooling to improve feature and model creation, evaluation, and trust.

Benefits

• Equity
• Health Insurance
• Remote Work

Culture

Requirements