Data Scientist (Masters)

Seattle

**Data Scientist (Masters) --- AI Data Trainer** **About The Role** What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the world's most advanced AI systems reason and solve problems? We're looking for Masters-level data scientists to challenge, audit, and refine cutting-edge AI models --- exposing their blind spots and helping build smarter, more reliable systems. This is a fully remote, flexible contract role. No prior AI industry experience needed --- just rigorous domain expertise and a sharp eye for technical quality. * Organization: Alignerr * Type: Hourly Contract * Location: Remote * Commitment: 10--40 hours/week **What You'll Do** * Design Advanced Challenges: Create complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more --- problems that genuinely stress-test AI reasoning * Author Ground-Truth Solutions: Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive benchmark for AI outputs * Audit AI-Generated Code: Evaluate code produced by AI models using libraries like Scikit-Learn, PyTorch, and TensorFlow --- assessing correctness, efficiency, and best practices * Identify Reasoning Failures: Spot logical flaws in AI outputs such as data leakage, overfitting, improper handling of imbalanced datasets, and flawed statistical conclusions * Provide Structured Feedback: Document failure modes clearly and systematically so model teams can directly improve AI reasoning and reliability **Who You Are** * Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a quantitative field with heavy emphasis on data analysis * Strong foundational expertise in supervised/unsupervised learning, deep learning, statistical inference, or big data technologies (Spark, Hadoop, etc.) * Able to communicate complex algorithmic concepts and statistical results clearly in writing * Naturally detail-oriented --- you catch errors in code syntax, mathematical notation, and statistical reasoning that others miss * Self-motivated and comfortable working independently on technical tasks * No prior AI or data annotation experience required **Nice to Have** * Prior experience with data annotation, data quality assurance, or model evaluation systems * Proficiency in production-level data science workflows such as MLOps or CI/CD for models * Familiarity with NLP techniques or large language model evaluation * Background in academic research or technical writing **Why Join Us** * Work directly with industry-leading AI research labs on genuinely frontier problems * Fully remote and flexible --- work when and where it suits you * Freelance autonomy with meaningful, intellectually stimulating task-based work * Make a tangible impact on how AI understands and solves complex data science problems * Potential for ongoing work and contract extension as new projects launch