Data Science Expert - AI Content Specialist

Data Science Expert – AI Content Specialist

About the Role

What if your deep knowledge of machine learning, statistics, and data engineering could directly shape the next generation of AI? We're looking for Data Science Experts to stress-test, evaluate, and refine advanced AI models — exposing weaknesses, authoring gold-standard solutions, and helping these systems reason better about the hardest problems in data science.

This is a fully remote, flexible contract role built for working data scientists, researchers, and advanced students 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, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
• Author Ground-Truth Solutions: Develop step-by-step, expert-level solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as definitive reference answers for AI training
• Audit AI-Generated Code: Critically evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing technical accuracy, efficiency, and correctness
• Refine AI Reasoning: Identify flaws in model logic — such as data leakage, overfitting, or mishandled class imbalance — and provide structured feedback that improves how the AI thinks and responds

Who You Are

• Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
• Deeply fluent in core data science concepts: supervised and unsupervised learning, deep learning, statistical inference, and big data technologies (e.g., Spark, Hadoop)
• Able to communicate complex algorithmic and statistical concepts clearly in writing
• Precise and detail-oriented when reviewing code syntax, mathematical notation, and statistical conclusions
• No prior AI or annotation experience required — your domain expertise is what matters

Nice to Have

• Experience with data annotation, data quality assurance, or model evaluation workflows
• Familiarity with production data science environments — MLOps, CI/CD pipelines for models, or similar
• Background in NLP, computer vision, or other applied ML domains

Why Join Us

• Work directly with industry-leading AI models at the frontier of research
• Fully remote and async — work when and where you choose
• Freelance autonomy with consistent, intellectually engaging task-based work
• Contribute to AI development that has a real and lasting impact on how these systems reason about data science
• Potential for ongoing work and contract extension as new projects launch