We are looking for experienced language professionals to support an ongoing project focused on reviewing and refining English (Canada) Translation Quality Rater customer service content.
Data Science Expert - AI Content Specialist
Job description
Data Science Expert – AI Content Specialist
About the Role
What if your expertise in machine learning, statistical inference, and data engineering could directly shape the intelligence of tomorrow's most powerful AI systems? We're looking for Data Science Experts to stress-test, evaluate, and improve cutting-edge AI models — working remotely on your own schedule.
This is a high-impact contractor role where your deep technical knowledge becomes the benchmark that AI has to meet. You won't just observe AI — you'll challenge it, expose its weaknesses, and help build something genuinely better.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Challenges — Create complex, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Author Ground-Truth Solutions — Develop rigorous, step-by-step solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as authoritative benchmarks for AI evaluation
- Audit AI-Generated Code — Critically review AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing them for correctness, efficiency, and best practices
- Refine AI Reasoning — Identify logical failures such as data leakage, overfitting, or mishandled class imbalance, then provide structured feedback that sharpens how the model thinks and responds
- Document Failure Modes — Systematically capture edge cases and reasoning breakdowns to help research teams 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 core areas: supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop)
- Able to communicate complex algorithmic and statistical concepts clearly in writing
- Highly precise when reviewing code syntax, mathematical notation, and statistical conclusions
- Self-directed and comfortable working independently on technical tasks
- 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 deployment
- Prior work reviewing or benchmarking AI/ML systems
Why Join Us
- Work directly with industry-leading large language models and AI research teams
- Fully remote and async — structure your work around your life, not the other way around
- Freelance autonomy with the substance of meaningful, technically rigorous work
- Contribute to AI development that sets the standard for how models reason about data science
- Potential for ongoing work and contract extension as new projects launch
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