Data Scientist (Masters)
Alignerr · United States
- Hybrid
- Contract
- $80,000 / year
- United States
Tailored resume — keyword-matched to this role.
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Job highlights
- Improve advanced AI systems through data science expertise.
- Design complex data science challenges for AI reasoning.
- Develop ground-truth solutions in Python, R, and SQL.
- Audit AI-generated code and identify failure modes.
- Work remotely on cutting-edge AI projects.
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
- Machine Learning
- Statistical Inference
- Data Engineering
- AI Development
- Python
- R
- SQL
- Scikit-Learn
- PyTorch
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 research and quantitative skills.
- Showcase technical skills: Emphasize ML, statistics, Python, R, and SQL experience.
- Demonstrate problem-solving: Provide examples of complex data analysis and solutions.
- Highlight remote work ability: Mention self-direction and asynchronous communication skills.
- Prepare for technical interviews: Be ready to discuss AI, data science concepts, and coding.
Technical preparation
Master core ML concepts: supervised/unsupervised learning.,Practice Python/R for data analysis and scripting.,Familiarize with Spark/Hadoop for big data tasks.,Review advanced statistical inference and Bayesian methods.
Behavioral questions
Describe a complex data problem you solved.,How do you ensure accuracy in your analysis?,How do you approach detailed code or math review?,How do you manage tasks independently and remotely?
Frequently asked questions
- What is the expected commitment for the Data Scientist AI Trainer role at Alignerr?
- The Data Scientist AI Trainer role at Alignerr is a flexible contract position requiring 10-40 hours per week. This allows for a good work-life balance while contributing to critical AI development.
- Does Alignerr require prior AI industry experience for this Data Scientist role?
- No, Alignerr does not require prior AI industry experience for this Data Scientist AI Trainer position. They are looking for deep, demonstrable expertise in data science, statistical inference, and machine learning.
- What are the primary responsibilities of a Data Scientist AI Trainer at Alignerr?
- As a Data Scientist AI Trainer, you will design advanced data science challenges, develop ground-truth solutions, audit AI-generated code, identify AI failure modes, and refine AI model reasoning.
- What educational background is required for the Data Scientist AI Trainer position?
- Alignerr is seeking candidates currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field with a strong emphasis on data analysis.
- Is this Data Scientist AI Trainer position a remote role?
- Yes, this Data Scientist AI Trainer position at Alignerr is a fully remote role, offering flexibility in terms of work location and schedule.
- What programming languages and libraries are important for the Data Scientist AI Trainer role?
- Proficiency in Python and R for developing solutions is key. Experience with libraries such as Scikit-Learn, PyTorch, and TensorFlow for auditing AI-generated code is also valuable.
- What are the 'nice to have' qualifications for an Alignerr Data Scientist AI Trainer?
- Nice-to-have qualifications include prior experience with data annotation, data quality assurance, evaluation systems, production-level data science workflows (MLOps, CI/CD), and familiarity with model evaluation frameworks.
- How does Alignerr support its remote Data Scientist AI Trainers?
- Alignerr offers a fully remote and flexible work environment, providing freelance autonomy with a task-based structure and international reach, allowing you to work on your own schedule from anywhere.