JOBSEARCHER

Data Scientist / Data Science Specialist $60 – $100/hr – Remote US

Grorapid LabsRemoteMay 23rd, 2026
Data Science ExpertsHourly contract · Remote · $60–$100 per hourRole Overview Contribute to a high-impact AI research initiative focused on advancing exploratory data analysis (EDA) capabilities in large language models. The role involves evaluating AI-generated analysis, designing structured rubrics, and producing gold-standard responses including statistical insights, visualizations, and executable Python code.Key ResponsibilitiesReview AI-generated exploratory data analysis outputs for accuracy and quality.Apply statistical methods and modeling techniques to validate insights across structured and unstructured datasets.Design prompts and detailed evaluation rubrics for fine-grained performance assessment.Deliver gold-standard examples, including clear visualizations, explanatory text, and Python notebooks.Translate data-driven reasoning and decision-making into clear, gradable criteria for AI training.Ideal QualificationsBachelor’s, Master’s, or PhD in Data Science, Computer Science, Statistics, Mathematics, or related field, OR 2+ years of industry experience in a data science role.Proficiency with Python and core data science libraries (pandas, numpy, scikit-learn).Strong foundation in statistical modeling, data analysis, and machine learning principles.Ability to identify meaningful patterns, trends, and associations within complex datasets.Excellent analytical writing skills with the ability to communicate insights clearly and concisely.Project DetailsStart: Immediate.Duration: 5–6 weeks.Commitment: Part-time, 10–20 hours/week (flexible).Schedule: Fully remote and asynchronous.Compensation & Contract$60–$100/hour USD, depending on experience.Top performers may receive bonus incentives of $20–$50/hour.Independent contractor engagement.Weekly payments via Stripe Connect.Application ProcessSubmit resume.Complete a short technical interview (25 minutes) including project-based conceptual questions and a Google Co-Lab data analysis exercise.