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Data Science Expert - AI Content Specialist

Job in Vancouver, BC, Canada
Listing for: Alignerr Corp.
Full Time position
Listed on 2026-10-11
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer, AI Evaluation
Job Description & How to Apply Below
Data Science Expert — AI Content Specialist
About

The Role
What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the world's most advanced AI systems reason and respond? We're looking for Data Science Experts to work with Alignerr — a team that partners with leading AI research labs to build and refine cutting-edge language models. Your job is to stress-test AI reasoning, author gold-standard solutions, and provide the kind of expert feedback that makes these models genuinely smarter.

This is a fully remote, flexible contract role built for data science professionals who want meaningful work on their own schedule.

Organization:
Alignerr

Type:
Hourly Contract

Location:

Remote

Commitment: 10–40 hours/week

What You'll Do

Design Advanced Challenges — Craft complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more

Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as the benchmark for AI responses

Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and Tensor Flow, assessing them for correctness, efficiency, and best practices

Sharpen AI Reasoning — Identify logical failures such as data leakage, overfitting, or improper handling of imbalanced datasets, and deliver structured feedback that improves how models think

Who You Are

Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field

Strong foundational expertise in core areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP

Able to communicate complex algorithmic concepts and statistical findings clearly in writing

Highly precise when reviewing code syntax, mathematical notation, and the validity of statistical conclusions

No prior AI or annotation experience required — your domain expertise is what matters

Nice to Have

Experience with data annotation, data quality workflows, or evaluation systems

Familiarity with production-level data science practices such as MLOps or CI/CD for models

Why Join Us

Work directly with industry-leading AI language models on problems that actually matter

Fully remote and asynchronous — work when and where it suits you

Freelance autonomy with the structure of meaningful, task-based projects

Contribute to AI development that shapes how these systems reason through real-world data science problems

Potential for ongoing work and contract extension as new projects launch
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