Data Scientist - AI Model Training & Evaluation

About The Role AI is only as good as the experts who evaluate it. We’re looking for data scientists to help train, evaluate, and improve next‑generation AI systems that are reshaping the world of technology. You’ll bring your deep expertise in statistics, machine learning, and data analysis to assess AI outputs, build evaluation frameworks, and ensure these systems deliver accurate, reliable, and unbiased results. This is a rare opportunity to work directly on the models powering the AI revolution — on your own schedule, from anywhere. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You’ll Do Evaluate AI model outputs for accuracy, reasoning quality, and statistical soundness Design and apply data‑driven evaluation criteria and scoring rubrics Analyze patterns in AI‑generated responses to identify systematic errors or biases Create high‑quality training data including prompts, solutions, and annotations in your areas of expertise Provide structured, detailed feedback to improve model performance across data science and analytical tasks Review AI‑generated code, visualizations, and statistical analyses for correctness Work independently and asynchronously on your own schedule Who You Are Degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field (MS or PhD preferred) Strong foundation in statistics, probability, and machine learning concepts Proficiency in Python, R, SQL, or similar data analysis tools Experience with data wrangling, exploratory data analysis, and model evaluation Excellent analytical thinking and sharp attention to detail Clear written communication in English — able to explain complex technical concepts simply Self‑motivated and comfortable working independently Nice to Have Experience with deep learning frameworks such as PyTorch or TensorFlow Familiarity with NLP, LLMs, or AI evaluation workflows Published research or industry experience in applied machine learning Background in A/B testing, causal inference, or experimental design Why Join Us Work on cutting‑edge AI projects shaping the future of technology Collaborate with top research labs and AI teams globally Fully remote and flexible — work on your own schedule, as much or as little as you like Gain deep, firsthand exposure to how state‑of‑the‑art LLMs are trained and evaluated Be part of a growing community of expert contributors making AI smarter and more reliable Potential for ongoing work and long‑term contract extension #J-18808-Ljbffr