Data Scientist (Masters)
Role summary
Alignerr is seeking a Data Scientist (Masters) to join their remote team as an AI Data Trainer. This hourly contract role involves developing advanced data science challenges, authoring ground-truth solutions using Python/R and SQL, and technically auditing AI-generated code and statistical analyses. The primary goal is to identify and document failure modes in AI models, particularly concerning machine learning theory, statistical inference, and neural network architectures, to improve their reasoning and accuracy. A Master's or PhD in a quantitative field is required, along with strong foundational knowledge in core data science areas and excellent analytical writing skills. No prior AI experience is necessary.
Data Scientist (Masters) - AI Data Trainer
- Location: Remote
About The Job
At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models.
You’ll challenge advanced language models on topics like machine learning theory, statistical inference, neural network architectures, and data engineering pipelines—documenting every failure mode so we can harden model reasoning.
Organization
: Alignerr
Position
: Data Scientist (Masters) - AI Data Trainer
Type
: Hourly Contract
Compensation
: $40–$80 /hour
Location
: Remote
Commitment
: 10–40 hours/week
What You’ll Do
- Develop Complex Problems: Design advanced data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction.
- Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as "golden responses."
- Technical Auditing: Evaluate AI-generated code (using libraries like Scikit-Learn, PyTorch, or TensorFlow), data visualizations, and statistical summaries for technical accuracy and efficiency.
- Refine Reasoning: Identify logical fallacies in AI reasoning—such as data leakage, overfitting, or improper handling of imbalanced datasets—and provide structured feedback to improve the model's "thinking" process.
Requirements
- Advanced Degree: Masters (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a heavy emphasis on data analysis.
- Domain Expertise: Strong foundational knowledge in core areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP.
- Analytical Writing: The ability to communicate highly technical algorithmic concepts and statistical results clearly and concisely in written form.
- Attention to Detail: High level of precision when checking code syntax, mathematical notation, and the validity of statistical conclusions.
- No AI experience required
Preferred
- Prior experience with data annotation, data quality, or evaluation systems
- Proficiency in production-level data science workflows (e.g., MLOps, CI/CD for models).
Why Join Us
- Excellent compensation with location-independent flexibility.
- Direct engagement with industry-leading LLMs.
- Contractor advantages: high agency, agility, and international reach.
- More opportunities for contracting renewals.
Application Process (Takes 15-20 min)
- Submit your resume
- Complete a short screening
- Project matching and onboarding
*PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.*