Data Scientist (Masters)

Alignerr Corp.

Cambridge

Remote

GBP 83,000 - 165,000

Part time

48 hours ago
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Job summary

Alignerr Corp. is seeking a Masters- or PhD-level Data Scientist to act as an AI Data Trainer. The role focuses on designing hard ML problems, authoring gold-standard solutions, and auditing AI model outputs with leading libraries. This is a fully remote, hourly contract with flexible hours and no required prior AI industry experience.

You'll work independently to challenge and improve advanced AI systems, leveraging your deep ML knowledge and rigorous statistical approach.

Qualifications

  • Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a heavily quantitative field.
  • Strong foundation in supervised and unsupervised learning, deep learning, and statistical modeling.
  • Comfortable with Python, R, or SQL and standard data science libraries and frameworks.
  • Able to communicate complex algorithmic concepts and statistical results clearly in writing.

Responsibilities

  • Design Advanced Challenges — craft complex data science problems across hyperparameter optimization, Bayesian inference, cross-validation, and more.
  • Author Ground-Truth Solutions — build rigorous, step-by-step technical solutions in Python/R, SQL, and mathematical derivations.
  • Audit AI-Generated Code — evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness and efficiency.
  • Identify Reasoning Failures — catch data leakage, overfitting, and imbalanced data issues, providing structured feedback.
  • Work Independently — complete task-based assignments on your own schedule, fully asynchronously.

Skills

Statistical modeling
Machine learning
Communication skills

Education

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

Tools

Python
R
SQL
Scikit-Learn
PyTorch
TensorFlow

Job description

Data Scientist (Masters) — AI Data Trainer
About The Role

What if your deep knowledge of machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason and respond?

We're looking for Masters-level data scientists to challenge, evaluate, and improve cutting-edge AI models — designing hard problems, authoring gold-standard solutions, and catching the subtle reasoning failures that only a true domain expert would spot.

This is a fully remote, flexible contract role. No prior AI industry experience required — just serious data science expertise and a sharp analytical mind.

  • 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 — Build rigorous, step-by-step technical solutions — Python/R scripts, SQL queries, mathematical derivations — that serve as definitive "golden responses" for model training
  • Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
  • Identify Reasoning Failures — Catch subtle flaws in AI logic — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that sharpens model reasoning
  • Work Independently — Complete task-based assignments on your own schedule, fully asynchronously
Who You Are
  • Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a heavily quantitative field
  • Strong foundational command of supervised and unsupervised learning, deep learning, and statistical modeling
  • Comfortable with Python, R, or SQL and standard data science libraries and frameworks
  • Able to communicate complex algorithmic concepts and statistical results clearly in writingNaturally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
  • No prior AI or data annotation experience required
Nice to Have
  • Familiarity with big data technologies like Spark or Hadoop
  • Experience with NLP or large-scale model development
  • Background in MLOps, CI/CD pipelines, or production-level data science workflows
  • Prior work in data annotation, data quality, or evaluation systems
Why Join Us
  • Work directly with industry-leading AI research labs on genuinely frontier problems
  • Fully remote and flexible — work when and where it suits you
  • Freelance autonomy with meaningful, intellectually stimulating work
  • Engage hands-on with the most advanced language models being built today
  • Potential for ongoing work and contract renewals as new projects launch
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