Data Scientist — Quality & Pipeline Intelligence
Data Science · Data Science & Analytics · United States · San Francisco, CA / Remote (USA) · Remote · Full-time · Mid-Senior (3+ yrs) · $130,000 – $165,000 + Equity
Develop algorithmic active learning data selection algorithms, model uncertainty filters, and anomaly detection models for complex training datasets.
Responsibilities
- Formulate active learning sampling algorithms that prioritize high-entropy data slices for human review
- Construct automated anomaly detection scripts identifying label drift, annotation noise, and guideline deviation
- Author statistical validation papers and client-facing performance scorecards for production deployments
- Partner closely with platform engineers to productionize data validation pipelines
Requirements
- B.S. or M.S. in Data Science, Statistics, Computer Science, or quantitative discipline
- Hands-on experience with Python, PyTorch / Scikit-Learn, and statistical hypothesis testing
- Experience handling unstructured data pipelines (images, audio, LiDAR point clouds, or text)
- Prior background in machine learning data curation or active learning is a major plus
Perks
- Top-of-market base salary and equity package
- Work with state-of-the-art foundation models and autonomous systems
- Comprehensive international health, dental, and vision insurance
- Annual in-person global company retreats