Protege is looking for a Senior Data Scientist to be at the heart of how we curate, assess, and prepare the training data that powers real-world AI systems. You'll lead the evaluation and optimization of large-scale datasets used to train state-of-the-art AI models.

What You'll Do

Design and apply statistical and machine learning methods to curate, filter, and enrich large-scale unstructured datasets
Develop frameworks to assess data diversity, duplication, and informativeness
Design statistical approaches to de-risk training datasets
Collaborate with model training teams to identify data bottlenecks and optimize dataset performance
Provide leadership on data quality strategy and shape internal best practices
Evaluate external datasets for integration, focusing on scalability, quality, and relevance to model performance
Help build data scorecards
Contribute to research and development of tools that automate data preprocessing and validation

What We're Looking For

PhD or equivalent Master's Degree + 4+ years industry experience in machine learning, economics, mathematics, engineering, computer science, statistics, or a related quantitative field
Strong understanding of AI model training pipelines, including pre-processing and evaluation
Experience working with large, unstructured datasets, especially text
Background in statistical analysis, bias detection, and data validation
Able to identify high-impact problems and drive independent solutions

Nice to Have

Experience with synthetic data generation or augmentation strategies
Publications or open-source contributions in data-centric AI or related areas
Experience developing evaluation frameworks or performance metrics for training data
Cross-functional collaboration with product, infrastructure, or partnership teams

Team & Environment

You will collaborate with research and engineering teams within our lean, fast-moving, high-trust environment. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.