Data Scientist QA Lead - Remote

The contract role is a remote Data Scientist Quality Assurance Lead for a rapidly expanding AI data‑services firm that creates training material for many of the world’s leading artificial‑intelligence companies and foundation‑model labs. The position focuses on safeguarding the consistency, accuracy, and overall quality of AI‑generated data‑science content and the work of trainers and reviewers. Day‑to‑day duties involve sampling and inspecting data‑science deliverables, pinpointing flaws, and delivering clear written feedback. You will assess code snippets, statistical reasoning, model‑selection choices, reproducibility, metric interpretation and business relevance against detailed rubrics. Communication with trainers and QA staff occurs mainly through Discord, where you will announce guideline updates, answer technical queries, and motivate inactive contributors. Additional tasks include drafting and maintaining style guides, FAQs, calibration exercises, onboarding resources, and tracking documents, as well as flagging systemic issues and proposing scalable quality‑control improvements. Candidates must hold a bachelor’s, master’s or doctoral degree in a quantitative discipline such as data science, statistics, computer science, machine learning, mathematics, economics or engineering. A minimum of three years’ experience in data‑science‑related roles—ranging from analytics and modeling to technical review or education—is required, together with a solid understanding of statistical methods, feature engineering, supervised and unsupervised learning, and model validation. Fluency in English and the ability to evaluate work against precise rubrics are essential. Preferred experience includes leading remote groups of trainers, annotators or engineers, familiarity with Python, pandas, NumPy, scikit‑learn, SQL, Jupyter, R, Spark, Git, MLflow and related cloud platforms, and prior involvement in AI‑training pipelines, data annotation or rubric‑based technical review. The role offers flexible remote work and the chance to join an expert network that will be tapped for future projects as they arise.