Data Scientist (Masters)

Alignerr; Montreal; Remote; CAD 69,000 - 124,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Freelance autonomy

Job summary

Alignerr Corp. is seeking a Data Scientist (Masters) to train AI models remotely. You will design complex ML problems, author reference solutions in Python/R and SQL, and audit AI outputs for accuracy. The role emphasizes rigorous statistical reasoning and documentation.

You should hold a Master's or PhD in a quantitative field, with expertise in supervised/unsupervised learning, deep learning, NLP, and big data tools. This is a remote, hourly contract with flexible hours and ongoing projects.

Qualifications

• Must hold a Master's or PhD in a quantitative field with strong data analysis focus.
• Experience with both supervised and unsupervised learning, deep learning, and NLP.
• Ability to write rigorous technical solutions in Python/R and SQL.

Responsibilities

• Design advanced data science problems to push AI reasoning and accuracy.
• Author ground-truth solutions with code, queries, and mathematical derivations.
• Audit AI-generated code for accuracy, efficiency, and correctness.
• Identify and document failure modes (data leakage, overfitting, imbalanced data).
• Refine model reasoning and document improvements for iterative development.

Skills

Supervised learning

Unsupervised learning

Deep learning

NLP

Python

SQL

Statistical inference

Model evaluation

Education

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

Tools

PyTorch

TensorFlow

Scikit-Learn

Spark

Hadoop

Job description

Data Scientist (Masters) — AI Model 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 through complex problems? We're looking for data scientists with advanced degrees to challenge, audit, and refine cutting‑edge AI models — helping them think more rigorously, reason more accurately, and perform at a higher level.

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

What You'll Do

• Design Advanced Challenges: Develop complex, domain‑specific data science problems spanning hyperparameter optimization, Bayesian inference, cross‑validation strategies, dimensionality reduction, and more — problems that genuinely push AI reasoning to its limits
• Author Ground‑Truth Solutions: Write rigorous, step‑by‑step technical solutions including Python and R scripts, SQL queries, and mathematical derivations that serve as authoritative reference answers
• Audit AI‑Generated Code: Evaluate AI outputs using libraries like Scikit‑Learn, PyTorch, and TensorFlow — assessing them for technical accuracy, efficiency, and correctness
• Identify and Document Failure Modes: Catch logical errors in AI reasoning such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback that improves model behaviour
• Refine Model Reasoning: Help shape how AI models approach statistical and algorithmic problems by documenting every meaningful failure and guiding iterative improvements

Who You Are

• Currently pursuing or have completed a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong data analysis focus
• Solid foundational knowledge across core areas such as supervised and unsupervised learning, deep learning, big data technologies (Spark, Hadoop), or NLP
• Able to communicate highly technical concepts — algorithmic logic, statistical results, mathematical derivations — clearly and precisely in written form
• Naturally detail‑oriented: you catch errors in code syntax, mathematical notation, and statistical reasoning that others miss
• Self‑directed and comfortable working independently on technical tasks
• No prior AI or data annotation experience required

Nice to Have

• Prior experience with data annotation, data quality assurance, or model evaluation systems
• Proficiency in production‑level data science workflows such as MLOps or CI/CD pipelines for machine learning models
• Familiarity with prompt engineering or working with large language models
• Experience writing technical documentation or academic‑style explanations of complex methods

Why Join Us

• Work directly with industry‑leading AI research teams and language models at the frontier of the field
• Fully remote and flexible — work when and where it suits you, on your own schedule
• Freelance autonomy with the structure of meaningful, technically rigorous work
• Make a direct, measurable impact on how the next generation of AI understands and applies data science
• Potential for ongoing work and contract extension as new projects launch