Data Scientist (Masters)

Alignerr Corp.; Melbourne; Remote; AUD 55,000 - 124,000; Full time

Job summary

Alignerr is seeking a Masters-level Data Scientist to design challenging data problems and audit AI models. You will craft rigorous, transparent solutions in Python/R and SQL, then audit outputs from Scikit-Learn, PyTorch, and TensorFlow.

The role emphasizes detecting data leakage, overfitting, and class imbalance, with remote, hourly engagement. Ideal candidates hold a Masters/PhD in a quantitative field, and can communicate complex results clearly in writing.

Qualifications

• Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a quantitative field.
• Strong foundation in supervised/unsupervised learning, deep learning, big data (Spark/Hadoop) or NLP.
• Able to communicate complex algorithms and statistics clearly in writing.
• Exceptionally detail-oriented with meticulous code and reasoning.
• Self-motivated and reliable when working independently and asynchronously.

Responsibilities

• Design advanced, domain-spanning data science problems to stress-test AI reasoning.
• Author rigorous, step-by-step solutions with Python/R, SQL, and derivations.
• Audit AI-generated code for accuracy, efficiency, and correctness.
• Refine AI reasoning by identifying data leakage, overfitting, and imbalance issues.
• Document failure modes to aid model hardening efforts.

Skills

Supervised learning

Unsupervised learning

Deep learning

NLP

Big data

Scala or Python scripting

Education

Masters/PhD in Data Science

Tools

Scikit-Learn

PyTorch

TensorFlow

Spark

Hadoop

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 Masters-level data scientists to challenge, audit, and improve cutting-edge AI models — exposing their blind spots and helping build more intelligent, reliable systems.

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

What You'll Do

• Design Advanced Challenges — Create complex, domain-spanning data science problems covering hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — tasks that genuinely stress-test AI reasoning
• Author Ground-Truth Solutions — Produce rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as authoritative "golden responses"
• Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing technical accuracy, efficiency, and correctness
• Refine AI Reasoning — Identify logical failures in AI outputs — data leakage, overfitting, mishandled class imbalance — and deliver structured feedback that improves how models think through data problems
• Document Failure Modes — Systematically record how and why advanced language models fail on technical tasks, contributing directly to model hardening efforts

Who You Are

• Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a heavily quantitative field
• Strong foundational knowledge across core areas — 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 reasoning that others miss
• Self-motivated and reliable when working independently and asynchronously
• No prior AI or data annotation experience required

Nice to Have

• Prior experience with data annotation, data quality workflows, or model evaluation systems
• Proficiency in production-level data science environments — MLOps, CI/CD for models, or similar
• Familiarity with prompt engineering or working alongside large language models
• Broad cross-domain knowledge spanning multiple subfields of data science or statistics

Why Join Us

• Work directly with industry-leading AI research labs on genuinely frontier problems
• Fully remote and flexible — work on your own schedule, from anywhere in the world
• Freelance autonomy with the structure of meaningful, technically challenging work
• Make a direct, traceable impact on how next-generation AI models reason through complex data science problems
• Potential for ongoing contract renewals as new projects launch