Data Science Expert - AI Content Specialist

Alignerr Corp.; Sydney; Remote; AUD 83,000 - 165,000; Part time

Job summary

Alignerr is seeking a Data Science Expert – AI Content Specialist to design advanced data science challenges and author authoritative solutions across Python/R, SQL, and mathematical derivations. You will audit model outputs from major libraries, identify failures in AI reasoning, and provide structured feedback for robust improvements.

The role is fully remote, hourly, with flexible hours (10–40 hours/week).

Qualifications

• 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 and statistical concepts clearly in writing
• Meticulous attention to detail — especially when reviewing code syntax, mathematical notation, and statistical validity
• Self-directed and comfortable working independently on technical tasks
• No prior AI or annotation experience required

Responsibilities

• Design Advanced Challenges — Craft complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
• Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as the definitive benchmark for AI responses
• Audit AI-Generated Code — Evaluate outputs from models using Scikit-Learn, PyTorch, TensorFlow, and other major libraries for correctness, efficiency, and best practices
• Refine AI Reasoning — Spot logical failures like data leakage, overfitting, and improper handling of class imbalance, then provide structured feedback that improves how AI models reason through problems
• Document Failure Modes — Systematically record where and how AI reasoning breaks down to help research teams build more robust models

Skills

Domain knowledge across ML & stats

Communication of complex concepts in w

Education

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

Tools

Python

R

SQL

Scikit-Learn

PyTorch

TensorFlow

Spark

Hadoop

NLP

Job description

Data Science Expert – AI Content Specialist

About The Role

What if your expertise in machine learning and statistical modeling could directly shape how the world's most advanced AI systems think and reason?

We're looking for experienced data scientists to work alongside leading AI research labs — designing challenges that push AI to its limits, authoring gold-standard solutions, and identifying the subtle reasoning failures that prevent AI from reaching its full potential.

This is a fully remote, flexible contract role. Your domain knowledge isn't just useful here — it's the whole point.

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

What You'll Do

• Design Advanced Challenges — Craft complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
• Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as the definitive benchmark for AI responses
• Audit AI-Generated Code — Evaluate outputs from models using Scikit-Learn, PyTorch, TensorFlow, and other major libraries for correctness, efficiency, and best practices
• Refine AI Reasoning — Spot logical failures like data leakage, overfitting, and improper handling of class imbalance, then provide structured feedback that improves how AI models reason through problems
• Document Failure Modes — Systematically record where and how AI reasoning breaks down to help research teams build more robust models

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 and statistical concepts clearly in writing
• Meticulous attention to detail — especially when reviewing code syntax, mathematical notation, and statistical validity
• 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 workflows, or evaluation systems
• Familiarity with production-level data science practices such as MLOps or CI/CD pipelines for models

Why Join Us

• Work directly with industry-leading AI language models at the frontier of AI research
• Fully remote and async-friendly — work on your own schedule, from anywhere
• Freelance autonomy with meaningful, intellectually stimulating work
• Contribute to AI development that has a real and lasting impact on how AI reasons about data and science
• Strong potential for ongoing work and contract renewal as new projects launch