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