Data Scientist (Masters)

Alignerr Corp.; Toronto; Remote; CAD 83,000 - 152,000; Part time

Job summary

Alignerr is seeking Masters- or PhD-level Data Scientists to stress-test and refine cutting-edge AI systems. You will design challenging datasets and evaluation tasks, write rigorous ground-truth solutions, and audit model code to ensure robust reasoning and correctness.

The role is remote, hourly, and freelance with flexible scheduling, offering opportunities for ongoing project work and expansion as new AI projects launch.

Qualifications

• Master's/PhD in Data Science, Statistics, CS or quantitative field with data-analysis focus.
• Strong knowledge in supervised/unsupervised learning, deep learning, NLP, and big data technologies (Spark/Hadoop).
• Ability to clearly describe complex algorithms and statistics to technical audiences.
• Detail-oriented; catches errors in code, notation, and reasoning.
• Self-motivated and capable of working independently.
• No prior AI or data annotation experience required.

Responsibilities

• Design data science challenges across domains—hyperparameter optimization, Bayesian inference, cross-validation, and dimensionality reduction.
• Author ground-truth solutions with Python/R scripts, SQL queries, and mathematical derivations.
• Audit AI-generated code and outputs using Scikit-Learn, PyTorch, and TensorFlow for accuracy and efficiency.
• Identify data leakage, overfitting, and imbalanced data issues; provide structured feedback to sharpen model reasoning.
• Work independently and asynchronously, on your own schedule.

Skills

Supervised learning

Unsupervised learning

Deep learning

NLP

Big data technologies

Education

Master's or PhD in Data Science or related

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 models think and reason? We're looking for Masters-level data scientists to challenge, stress-test, and refine cutting-edge AI systems — helping ensure they reason correctly, write clean code, and handle complex problems with precision.

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

What You'll Do

• Design complex data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction — pushing AI models to their limits
• Author rigorous ground-truth solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for model evaluation
• Audit AI-generated code and outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing technical accuracy, efficiency, and correctness
• Identify and document reasoning failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback to sharpen model reasoning
• Work independently and asynchronously — fully on your own schedule

Who You Are

• Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis
• Deeply knowledgeable in core areas such as supervised and unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
• Able to write clearly and precisely about complex algorithmic concepts and statistical results for technical audiences
• Naturally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical reasoning that others miss
• Self-motivated and consistent when working independently
• No prior AI or data annotation experience required

Nice to Have

• Experience with data annotation, data quality evaluation, or AI evaluation systems
• Proficiency in production-level data science workflows such as MLOps or CI/CD for models
• Familiarity with model benchmarking or technical content authoring
• Background spanning multiple data science subfields — the broader your expertise, the more impactful your contributions

Why Join Us

• Work directly with industry-leading AI research labs on cutting-edge model development
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, task-based work
• Make a direct, tangible impact on how advanced AI models reason about data science
• Potential for ongoing work and contract extension as new projects launch