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 by testing their reasoning.
- Design complex data science challenges for AI.
- Develop ground-truth solutions with Python, R, and SQL.
- Audit AI-generated code for accuracy and efficiency.
- Identify and fix AI model failure modes.
About the role
Data Scientist AI 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 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 Scientist AI Trainer
- Machine Learning
- Statistical Inference
- Data Engineering
- AI Models
- Python
- R
- SQL
- Scikit-Learn
- PyTorch
- TensorFlow
Skills & topics
- Data Scientist
- AI Trainer
- Machine Learning
- Statistical Inference
- Data Engineering
- Python
- R
- SQL
- Remote
- Contract
How to get hired
- Tailor your resume: Highlight your Master's or PhD in a quantitative field and specific data science skills like machine learning, statistical inference, and Python/R/SQL.
- Showcase problem-solving: Emphasize your ability to design complex challenges and create rigorous solutions, demonstrating your technical communication skills.
- Emphasize remote work readiness: Clearly state your experience working independently in asynchronous, remote environments.
- Prepare for technical questions: Be ready to discuss your experience with core data science areas and specific libraries like Scikit-Learn, PyTorch, and TensorFlow.
Technical preparation
Master core ML algorithms and statistical methods.,Practice Python/R for data analysis and modeling.,Solve complex data challenges independently.,Familiarize with Scikit-Learn, PyTorch, TensorFlow.
Behavioral questions
Describe a complex data problem you solved.,How do you ensure accuracy in your work?,How do you communicate technical findings clearly?,How do you manage your time remotely?
Frequently asked questions
- What specific data science skills are most critical for the Data Scientist AI Trainer role at Alignerr?
- For the Data Scientist AI Trainer position at Alignerr, critical skills include a strong foundation in machine learning, statistical inference, and data engineering. Proficiency in Python and R for scripting, along with SQL for data manipulation, is essential. Experience with libraries like Scikit-Learn, PyTorch, and TensorFlow is also highly valued for auditing AI-generated code and refining model reasoning.
- Does Alignerr require prior AI industry experience for the Data Scientist AI Trainer position?
- No, Alignerr explicitly states that prior AI industry experience is not required for the Data Scientist AI Trainer role. The primary requirement is deep, demonstrable expertise in data science, along with graduate-level training.
- What is the work arrangement for the Data Scientist AI Trainer role at Alignerr?
- The Data Scientist AI Trainer role at Alignerr is a fully remote, flexible contract position. You can work on your own schedule, from anywhere, offering freelance autonomy.
- How does Alignerr assess candidates for the Data Scientist AI Trainer role?
- Alignerr assesses candidates based on their graduate-level training, strong foundational knowledge in core data science areas, and their ability to communicate technical concepts clearly. They also look for detail-oriented individuals comfortable working independently in a remote setting.
- What kind of technical challenges can I expect to work on as a Data Scientist AI Trainer at Alignerr?
- As a Data Scientist AI Trainer, you will design and solve complex data science problems. These can involve hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction, all aimed at pushing AI reasoning to its limits.
- Is the Data Scientist AI Trainer role at Alignerr a full-time or part-time position?
- The Data Scientist AI Trainer role at Alignerr is an hourly contract position with a commitment of 10–40 hours per week, offering flexibility in workload.