Data Scientist (Masters)

Data Scientist (Masters) — AI Data Trainer About The Role What if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason through complex problems? We're looking for data scientists with graduate-level training to challenge, audit, and improve cutting-edge AI models — stress-testing their reasoning, exposing their blind spots, and helping build the gold-standard solutions they learn from. This is hands-on, intellectually demanding work that puts your domain knowledge at the centre of frontier AI development. This is a fully remote, flexible contract role. No prior AI industry experience required — just deep, demonstrable expertise in data science. • Organization: Alignerr • Type: Hourly Contract • Location: Remote • Commitment: 10–40 hours/week What You'll Do • Design Advanced Challenges — Craft complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — problems that genuinely push AI reasoning to its limits • 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 responses • Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical accuracy, efficiency, and correctness across code, visualizations, and statistical summaries • Identify and Document Failure Modes — Spot logical errors in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured, actionable feedback that directly improves model performance • Refine Model Reasoning — Work iteratively with AI outputs to harden the model's analytical thinking across the full data science pipeline Who You Are • Currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis • Strong foundational knowledge across core areas — supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP • Able to communicate highly technical concepts — algorithmic logic, statistical results, mathematical derivations — with clarity and precision in writing • Naturally detail-oriented when reviewing code syntax, mathematical notation, and the validity of statistical conclusions • Self-directed and comfortable working independently in an async, remote environment • No prior AI or data annotation experience required Nice to Have • Prior experience with data annotation, data quality assurance, or evaluation systems • Proficiency in production-level data science workflows — MLOps, CI/CD for models, experiment tracking • Familiarity with model evaluation frameworks or benchmark design Why Join Us • Work directly on frontier AI projects alongside world-leading research labs • Fully remote and flexible — work on your own schedule, from anywhere • Freelance autonomy: high agency, task-based structure, and international reach • Engage hands-on with the most capable large language models available today • Potential for ongoing contract renewals as new projects launch