Remote Data Scientist — AI Model Trainer (Masters)

Alignerr Corp.; Christchurch; Remote; GBP 55,000 - 96,000; Full time

Job summary

Alignerr seeks a Data Scientist (Masters) to help train and evaluate cutting-edge AI models. This fully remote, hourly contract role focuses on designing challenging data science problems and producing rigorous solutions.

You will audit AI-generated code with libraries like Scikit-Learn, PyTorch, and TensorFlow, and provide precise feedback to improve model reasoning. 10–40 hours per week, flexible schedule.

Qualifications

• Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
• Strong foundational knowledge across core data science domains: supervised/unsupervised learning, deep learning, big data tech or NLP.
• Able to communicate complex algorithmic and statistical concepts clearly in writing.
• Highly detail-oriented with careful attention to code syntax and mathematical notation.
• Self-motivated and reliable when working independently.
• No prior AI training or annotation experience required.

Responsibilities

• Design advanced, domain-spanning data science challenges including hyperparameter optimization and cross-validation.
• Author ground-truth solutions with Python/R scripts, SQL queries, and mathematical derivations.
• Audit AI-generated code for correctness and efficiency using Scikit-Learn, PyTorch, and TensorFlow.
• Refine AI reasoning by identifying data leakage, overfitting, or imbalanced datasets and provide actionable feedback.
• Work independently on task-based assignments with flexible scheduling.

Skills

Python

SQL

Statistics

Deep learning

Education

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

Tools

Scikit-Learn

PyTorch

TensorFlow

Job description

Alignerr seeks a Data Scientist (Masters) to help train and evaluate cutting-edge AI models. This fully remote, hourly contract role focuses on designing challenging data science problems and producing rigorous solutions.

You will audit AI-generated code with libraries like Scikit-Learn, PyTorch, and TensorFlow, and provide precise feedback to improve model reasoning. 10–40 hours per week, flexible schedule.