Data Science Expert - AI Content Specialist

Data Science Expert – AI Content SpecialistAbout The Role What if your data science expertise could directly shape how the world's most advanced AI models think, reason, and solve problems? We're looking for experienced data scientists to work alongside leading AI research teams — designing complex challenges, authoring expert solutions, and auditing AI-generated work to push the boundaries of what AI can do. This is a fully remote, flexible contract role built for serious data science practitioners who want meaningful, intellectually stimulating work on their own schedule.

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

What You'll Do

• Design Advanced Challenges — Create rigorous data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
• Author Ground-Truth Solutions — Develop step-by-step expert solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive benchmark for AI responses
• Audit AI-Generated Code — Evaluate code written using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
• Refine AI Reasoning — Identify flaws in AI logic — such as data leakage, overfitting, or mishandled class imbalance — and provide structured feedback that improves model reasoning at a fundamental level
• Document Failure Modes — Surface and record how AI models break down on complex technical topics so research teams can harden model performance

Who You Are

• Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
• Strong foundational knowledge across supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
• Able to communicate complex algorithmic concepts and statistical results clearly and concisely in writing
• Highly precise — you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
• Self-motivated and reliable when working independently on task-based assignments
• No prior AI or annotation experience required

Nice to Have

• Experience with data annotation, data quality assurance, or evaluation systems
• Familiarity with production-level data science workflows — MLOps, CI/CD pipelines for models, or model monitoring
• Prior work auditing or benchmarking machine learning systems

Why Join Us

• Work directly with industry-leading AI research labs on cutting-edge model development
• Fully remote and asynchronous — work when and where it suits you
• Freelance autonomy with consistent, intellectually rewarding task-based work
• Contribute to AI that will influence how advanced models reason about data science for years to come
• Potential for ongoing work and contract extension as new projects launch