Data Science & Analysis - AI Training - Columbus, US

Role overview Apply professional data science or analytics judgment to help assess and improve AI systems through paid, project-based evaluation tasks. Work can involve reviewing model-generated insights, validating statistical reasoning, and checking code outputs. Candidates first complete a short skills assessment; suitable participants may then receive tasks of varying lengths, including some that require an uninterrupted hour.

Responsibilities - Review AI-generated data analyses for correctness, clarity, and completeness. - Check mathematical and statistical claims against authoritative references. - Execute data scripts in Python or R to verify outputs and test edge cases. - Record strengths and weaknesses in model reasoning about data and predictive methods. - Confirm that responses comply with task guidance and expected professional standards.

Requirements - A bachelor’s, master’s, or doctoral degree in data science, statistics, mathematics, or a closely related quantitative subject. - Real-world experience in analytics, predictive modeling, or machine learning engineering. - Ability to work through challenging statistical problems and interpret sophisticated data visualizations independently. - Strong attention to detail and skill in identifying flawed statistical logic or data interpretation. - Significant use of large language models in data workflows and understanding of common failure modes. - Concise communication of mathematical concepts and analytical findings, plus a PayPal account for payment.

Nice to have - Python skills, including pandas, NumPy, or scikit-learn, or R; advanced SQL; experience with Tableau, Power BI, Matplotlib, or Seaborn; and knowledge of machine learning frameworks such as PyTorch or TensorFlow.

Benefits and work setup Work is flexible and remote, with task duration varying; some assignments need a full uninterrupted hour. Rates depend on the project, and the listing notes that certain tasks may pay up to $80 per hour.