Data Science Expert - AI Content Specialist

About The Role

What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the world's most advanced AI models think and reason? We're looking for Data Science Experts to challenge, audit, and improve cutting-edge AI systems — working remotely, on your own schedule, alongside leading AI research labs.

This is your opportunity to apply your expertise at the frontier of AI development, where your analytical instincts and technical precision have a measurable, lasting impact.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

• Design Advanced Challenges: Craft complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — problems that push AI models to their limits
• Author Ground-Truth Solutions: Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as authoritative reference answers
• Audit AI-Generated Code: Evaluate AI outputs across libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing technical accuracy, efficiency, and correctness of data visualizations and statistical summaries
• Refine AI Reasoning: Identify and document logical failures in AI reasoning — such as data leakage, overfitting, or improper handling of imbalanced datasets — and provide structured feedback to improve model decision-making

• Advanced Degree: Pursuing or completed a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis
• Domain Expert: Deep foundational knowledge in areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
• Clear Technical Communicator: Able to explain complex algorithmic concepts and statistical results in precise, well-structured written form
• Detail-Oriented: High attention to precision when checking code syntax, mathematical notation, and the validity of statistical conclusions
• No prior AI experience required — your data science expertise is what matters

• Experience with data annotation, data quality assurance, or evaluation systems
• Proficiency in production-level data science workflows such as MLOps or CI/CD pipelines for models
• Familiarity with prompt engineering or AI model evaluation frameworks

• Work directly with industry-leading large language models at the cutting edge of AI research
• Fully remote and asynchronous — work when and where it suits you
• Freelance autonomy with the depth of meaningful, technically challenging work
• High agency over your workload with flexible weekly commitments
• Contribute to AI development that shapes how intelligent systems reason about data science for years to come
• Potential for ongoing work and contract extension as new projects launch