Research Scientist, Foundational Data Science
Tasks
- Assess dataset defects and signal corruption
- Build automated agentic pipeline with human in the loop
- Build evaluation harnesses and experiment frameworks
- Design benchmarks for real-world performance
- Develop dataset and benchmark suites
- Implement baseline and competitor models
- Invent tabular foundation model tools
- Publish frontier research results
- Scale tabular foundation model capabilities
Perks/Benefits
- Inclusive work environment
- Professional research publications
- Remote work option
- Travel opportunities
Skills/Tech-stack
Benchmarking | Data Leakage Mitigation | Data Modeling | Data Quality | Data leakage | Dataset Leakage Detection | Deep learning | Distribution Shift | Distribution Shift Detection | Evaluation | Experimentation | Gradient boosting | Human-in-the-loop | Label Noise | Label Noise Detection | Leakage detection | Leakage mitigation | Machine Learning | Tabular Data | Tabular Data Modeling | The Loop | XGBoost
Education
Regions
Countries
States
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