Data Science Expert - AI Content Specialist

Alignerr Corp.; New Zealand; Remote; NZD 83,000 - 165,000; Part time

Job summary

Alignerr is seeking a Data Science Expert specialized in AI content evaluation to stress-test and improve cutting-edge AI models. You will work remotely on your own schedule as part of a high-impact contractor role.

Design challenges, author ground-truth solutions with Python/R and SQL, audit AI-generated code, and provide feedback to reduce data leakage and overfitting, helping models reason better.

Qualifications

• Pursuing or holding a Master’s/PhD in Data Science or related field.
• Strong knowledge in supervised/unsupervised learning, deep learning, NLP, or big data tech.
• Clear written communication of complex concepts; precise review of code and math.

Responsibilities

• Design advanced, domain-specific data science challenges across hyperparameter optimization, Bayesian inference, CV, and more.
• Author ground-truth solutions with Python/R, SQL, and mathematical derivations for AI benchmarks.
• Audit AI-generated code using Scikit-Learn, PyTorch, TensorFlow for correctness and efficiency.
• Refine AI reasoning by identifying data leakage, overfitting, and class imbalance; provide structured feedback.
• Document failure modes to help teams harden model performance.

Skills

Machine learning

Statistical inference

Data engineering

Python

Education

Master's or PhD in Data Science/Statistics/CS

Tools

Scikit-Learn

PyTorch

SQL

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