2 days ago

Data Scientist (Masters)

Alignerr

Melbourne

2 days ago

Apply

Alignerr is seeking Masters-level data scientists for a fully remote, flexible contract role as an AI Data Trainer. The position involves designing advanced data science challenges, authoring ground-truth solutions, auditing AI-generated code, and refining AI reasoning to improve cutting-edge AI models. Requires strong foundational knowledge in machine learning, statistics, and data engineering, with excellent written communication skills.

Core AIRemoteContractEntry LevelMachine LearningStatistical Inference

Data Scientist (Masters)

Apply

Core AIRemoteContractEntry LevelMachine Learning

Salary

Not specified

Work Location

Melbourne, Victoria, Australia, AU

Work Model

Fully remote, flexible contract role; work from anywhere in the world

Employment Type

Hourly Contract

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

Machine LearningStatistical InferenceData EngineeringHyperparameter OptimizationBayesian InferenceCross-ValidationDimensionality ReductionPythonRSQLScikit-LearnPyTorchTensorFlowApache SparkApache Hadoop

Soft Skills

Written CommunicationDetail-OrientedSelf-MotivatedReliableIndependent WorkAsynchronous Collaboration

Preferred Qualifications

Technical (Nice-to-have)

Data AnnotationData Quality WorkflowsModel Evaluation SystemsMLOpsCI/CDPrompt EngineeringLarge Language Models

Key Responsibilities

•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

Data ScienceAIMachine LearningRemoteContractPythonSQLStatisticsData EngineeringAI Training

Core Qualifications

Technical (Must-have)

Soft Skills

Written CommunicationDetail-OrientedSelf-MotivatedReliableIndependent WorkAsynchronous Collaboration

Key Responsibilities

•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