Data Scientist (Masters)

Alignerr Corp.; Brisbane; Remote; AUD 55,000 - 110,000; Part time

Job summary

Alignerr is seeking a Data Scientist with a Masters to challenge, evaluate, and sharpen cutting-edge AI models. You will design complex challenges and author ground-truth solutions using Python/R, SQL, and mathematical derivations.

This fully remote contract role offers flexible hours (10–40 hours/week) and the chance to work with state-of-the-art language models, documenting failure modes and delivering actionable feedback.

Qualifications

• Pursuing or holding a Master's or PhD in Data Science, Statistics, CS, or a quantitative field.
• Strong knowledge of supervised and unsupervised learning, deep learning, big data tech (Spark/Hadoop), or NLP.
• Able to communicate complex algorithmic concepts and statistical results clearly in writing.
• Exceptionally detail-oriented and able to work independently and asynchronously.

Responsibilities

• Design Complex Challenges: Create advanced, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — problems that genuinely push AI to its limits
• 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 'golden' benchmark responses
• Audit AI-Generated Code: Critically evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness
• Refine AI Reasoning: Diagnose logical failures in AI outputs — data leakage, overfitting, improper handling of imbalanced datasets — and deliver structured, actionable feedback that improves how models think
• Document Failure Modes: Systematically capture how and where AI reasoning breaks down across machine learning theory, statistical inference, neural network architectures, and data engineering pipelines

Skills

Machine Learning

Statistical Inference

Data Analysis

Education

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

Tools

Scikit-Learn

PyTorch

TensorFlow

SQL

Job description

Data Scientist (Masters) — AI Data Trainer

About The Role

What if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason and respond? We're looking for Data Scientists with graduate-level training to challenge, evaluate, and sharpen cutting-edge AI models — identifying where they fail, why they fail, and how to make them better.

This is a fully remote, flexible contract role. No prior AI industry experience required — just deep, battle-tested knowledge of data science and the ability to communicate it with precision.

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

What You'll Do

• Design Complex Challenges: Create advanced, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — problems that genuinely push AI to its limits
• 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 "golden" benchmark responses
• Audit AI-Generated Code: Critically evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness
• Refine AI Reasoning: Diagnose logical failures in AI outputs — data leakage, overfitting, improper handling of imbalanced datasets — and deliver structured, actionable feedback that improves how models think
• Document Failure Modes: Systematically capture how and where AI reasoning breaks down across machine learning theory, statistical inference, neural network architectures, and data engineering pipelines

Who You Are

• Currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with strong emphasis on data analysis
• Deep foundational knowledge across supervised and unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
• Able to communicate complex algorithmic concepts and statistical results clearly and precisely in writing
• Exceptionally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical logic that others miss
• Comfortable working independently and asynchronously on technically demanding tasks
• No prior AI or AI training experience required

Nice to Have

• Prior experience with data annotation, data quality evaluation, or AI evaluation systems
• Proficiency in production-level data science workflows — MLOps, CI/CD for models, or similar
• Familiarity with prompt engineering or language model evaluation
• Experience writing technical documentation or educational content for technical audiences

Why Join Us

• Work directly with industry-leading AI research labs on genuinely frontier problems
• Fully remote and flexible — structure your hours around your life, not the other way around
• Freelance autonomy with consistent, meaningful technical work
• Engage with the most advanced language models in existence and see your contributions shape their capabilities
• Potential for ongoing contract renewals and expanded project involvement as new work launches