Data Scientist (Masters)
Alignerr · United States
- Hybrid
- Contract
- $80,000 / year
- United States
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Job highlights
- Improve advanced AI reasoning capabilities.
- Design complex data science challenges.
- Develop rigorous ground-truth solutions.
- Audit AI-generated code and outputs.
- Remote, flexible, hourly contract role.
About the role
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 Model Auditing
- Python
- R
- SQL
- Data Analysis
- Quantitative Research
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 master's/PhD level data science skills and quantitative experience.
- Showcase technical expertise: Emphasize ML, statistical inference, Python, R, and SQL skills.
- Demonstrate remote readiness: Detail your self-direction and async communication abilities.
- Prepare for technical screening: Be ready to discuss complex data science problems and solutions.
- Highlight analytical rigor: Showcase your attention to detail in code and math review.
Technical preparation
Master core ML algorithms and statistical methods.,Practice Python/R for data analysis and modeling.,Review SQL for data querying and manipulation.,Understand concepts like overfitting and data leakage.
Behavioral questions
Describe a complex technical problem you solved.,How do you ensure accuracy in your work?,How do you work independently and manage tasks?,How do you communicate technical findings clearly?
Frequently asked questions
- What is the difference between this role and a typical Data Scientist job at Alignerr?
- This Data Scientist AI Trainer role at Alignerr focuses on auditing and improving AI models rather than traditional data analysis or product development. You'll be stress-testing AI reasoning, identifying failure modes, and creating benchmark solutions for cutting-edge AI systems.
- Is prior experience with AI or machine learning required for the Data Scientist AI Trainer role at Alignerr?
- No, prior AI industry experience is not required. Alignerr seeks deep, demonstrable expertise in core data science areas such as machine learning, statistical inference, and data engineering. Your advanced academic training is the key qualification.
- What kind of data science expertise is most valuable for this remote contract role at Alignerr?
- The most valuable expertise for this role at Alignerr includes a strong foundation in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), NLP, statistical inference, and data engineering. Experience with Python, R, and SQL is also crucial for developing ground-truth solutions.
- How does Alignerr ensure fairness and accuracy in AI models through this role?
- Alignerr's Data Scientist AI Trainers ensure fairness and accuracy by designing advanced challenges, authoring rigorous ground-truth solutions, auditing AI-generated code, identifying failure modes, and iteratively refining model reasoning. This structured approach directly improves AI performance and reliability.
- What are the typical work hours and flexibility for a Data Scientist AI Trainer at Alignerr?
- This is a fully remote, flexible hourly contract role at Alignerr, with commitment ranging from 10–40 hours per week. You can work on your own schedule, from anywhere, offering significant autonomy.
- What academic background does Alignerr look for in a Data Scientist AI Trainer?
- Alignerr is looking for candidates currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a closely related quantitative field with a strong emphasis on data analysis and research.