Research Data Scientist

📋 Description Identify and evaluate high-value data sources for ML training and evaluation Design synthetic data generation using SCMs, probabilistic models, or simulators Build tools/workflows to generate, validate, and iterate on synthetic data at scale Develop metrics and evaluation procedures for synthetic data quality Transform data into formats accessible for training and evaluating large-scale ML models Collaborate with research and engineering to maintain scalable, reproducible data pipelines 🎯 Requirements Synthetic data generation for ML, especially structured/tabular data Structural Causal Models and probabilistic/simulation-based data generation Identifying and evaluating high-quality data sources for training/evaluating ML models Bringing data from structured and unstructured sources into ML-ready formats Designing analyses to assess data quality, realism, diversity, and bias Python data processing and scientific computing stack (numpy, pandas, scipy, scikit-learn) 🎁 Benefits Competitive compensation with salary and equity Comprehensive health coverage for you and your dependents Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys Relocation support for employees moving to join the team Mission-driven, low-ego culture valuing diversity and action