Data Scientist (Masters)
Alignerr · United States
- Hybrid
- Contract
- $75,000 / year
- United States
Tailored resume — keyword-matched to this role.
Hiring manager — we find who's hiring.
Intro email — drafted to reach them directly.
Job highlights
- Improve cutting-edge AI systems through data science expertise.
- Design complex data science challenges for AI models.
- Author ground-truth solutions in Python, R, and SQL.
- Identify and document AI reasoning failures.
- Work remotely on frontier AI development projects.
About the role
Data Scientist AI Trainer
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 graduate-level training to challenge, audit, and improve cutting-edge AI models — stress-testing their reasoning, exposing their blind spots, and helping build the gold-standard solutions they learn from. This is hands-on, intellectually demanding work that puts your domain knowledge at the centre of frontier AI development.
This is a fully remote, flexible contract role. No prior AI industry experience required — just deep, demonstrable expertise in data science.
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 — problems that genuinely push AI reasoning to its limits.
- Author Ground-Truth Solutions: Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive benchmark for AI responses.
- Audit AI-Generated Code: Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical accuracy, efficiency, and correctness across code, visualizations, and statistical summaries.
- Identify and Document Failure Modes: Spot logical errors in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured, actionable feedback that directly improves model performance.
- Refine Model Reasoning: Work iteratively with AI outputs to harden the model's analytical thinking across the full data science pipeline.
Who You Are
- Currently 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.
- Strong foundational knowledge across core areas — supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP.
- Able to communicate highly technical concepts — algorithmic logic, statistical results, mathematical derivations — with clarity and precision in writing.
- Naturally detail-oriented when reviewing code syntax, mathematical notation, and the validity of statistical conclusions.
- Self-directed and comfortable working independently in an async, remote environment.
- No prior AI or data annotation experience required.
Nice to Have
- Prior experience with data annotation, data quality assurance, or evaluation systems.
- Proficiency in production-level data science workflows — MLOps, CI/CD for models, experiment tracking.
- Familiarity with model evaluation frameworks or benchmark design.
Why Join Us
- Work directly on frontier AI projects alongside world-leading research labs.
- Fully remote and flexible — work on your own schedule, from anywhere.
- Freelance autonomy: high agency, task-based structure, and international reach.
- Engage hands-on with the most capable large language models available today.
- Potential for ongoing contract renewals as new projects launch.
Key skills/competency
- Data Science
- Machine Learning
- Statistical Inference
- Data Engineering
- AI Models
- Python
- R
- SQL
- Model Auditing
- AI Reasoning
Skills & topics
- Data Scientist
- AI Trainer
- Machine Learning
- Statistical Inference
- Data Engineering
- Python
- R
- SQL
- AI Model Auditing
- Remote Work
How to get hired
- Tailor your resume: Highlight your Master's or PhD-level data science skills, statistical inference, and data engineering experience.
- Showcase your portfolio: Include projects demonstrating your ability to design challenges and author solutions in Python/R/SQL.
- Emphasize remote work skills: Detail your self-direction and comfort with async, independent work.
- Prepare for technical questions: Be ready to discuss core data science concepts and model auditing.
Technical preparation
Master core ML algorithms and statistical concepts.,Practice coding Python/R for data analysis.,Understand SQL for data manipulation.,Familiarize with model evaluation techniques.
Behavioral questions
Describe a complex data problem you solved.,How do you ensure accuracy in your work?,How do you communicate technical findings?,How do you manage independent, remote work?
Frequently asked questions
- What specific data science skills are most important for the Data Scientist AI Trainer role at Alignerr?
- For the Data Scientist AI Trainer position at Alignerr, the most crucial skills include machine learning, statistical inference, and data engineering. A strong understanding of supervised/unsupervised learning, deep learning, big data technologies (like Spark/Hadoop), and NLP is highly valued. Your ability to design complex data science challenges and author rigorous ground-truth solutions in Python, R, or SQL will be key.
- Is prior AI industry experience required for the Data Scientist AI Trainer job at Alignerr?
- No, prior AI industry experience is not required for the Data Scientist AI Trainer role at Alignerr. The company emphasizes deep, demonstrable expertise in data science. They are looking for individuals with graduate-level training who can apply their existing skills to audit and improve AI models, rather than those with previous AI-specific backgrounds.
- What is the work arrangement for the Data Scientist AI Trainer position at Alignerr?
- The Data Scientist AI Trainer position at Alignerr is a fully remote, flexible contract role. You can work on your own schedule, from anywhere. This offers freelance autonomy with a task-based structure and international reach.
- What educational background is needed for the Data Scientist AI Trainer role at Alignerr?
- To be considered for the Data Scientist AI Trainer position at Alignerr, you should be currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or another quantitative field with a strong emphasis on data analysis. Graduate-level training is a key requirement.
- How will I be evaluated as a Data Scientist AI Trainer at Alignerr?
- As a Data Scientist AI Trainer at Alignerr, your work will involve designing advanced challenges, authoring ground-truth solutions, auditing AI-generated code, identifying failure modes in AI reasoning, and refining AI model outputs. Your contributions will directly improve the performance and analytical thinking of cutting-edge AI models.