Alignerr
Data Scientist (Masters)
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Data Scientist (Masters)
Data Scientist (Masters) — AI Data Trainer
About The Role
What if your deep knowledge of machine learning, statistical inference, and data engineering could directly shape how the world’s most advanced AI systems reason and respond?
We’re looking for Masters-level data scientists to challenge, evaluate, and improve cutting-edge AI models—designing hard problems, authoring gold-standard solutions, and catching the subtle reasoning failures that only a true domain expert would spot.
This is a fully remote, flexible contract role. No prior AI industry experience required—just serious data science expertise and a sharp analytical mind.
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
- Author ground-truth solutions—build rigorous, step-by-step technical work, including:
- Python/R scripts
- SQL queries
- Mathematical derivations
- Serving as definitive "golden responses" for model training
- Audit AI-generated code—evaluate outputs using:
- Scikit-Learn
- PyTorch
- TensorFlow For technical correctness, efficiency, and best practices
- Identify reasoning failures—catch subtle flaws in AI logic, such as:
- Data leakage
- Overfitting
- Improper handling of imbalanced datasets
- Provide structured feedback to sharpen model reasoning
- Work independently—complete task-based assignments on your own schedule in a fully asynchronous format
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Who You Are
- Pursuing or holding a Masters or PhD in:
- Data Science
- Statistics
- Computer Science
- A directly quantitative field
- Strong foundational understanding of:
- Supervised and unsupervised learning
- Deep learning
- Statistical modeling
- Proficiency with:
- Python, R, or SQL
- Standard data science libraries and frameworks
- Ability to communicate complex algorithmic concepts and statistical results clearly in writing
- Extremely detail-oriented—capable of catching errors in:
- Code syntax
- Mathematical notation
- Statistical conclusions
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No Prior Experience Required:
❏ AI or data annotation industry background
Nice to Have
- Experience with big data technologies (Spark, Hadoop)
- Background in NLP (Natural Language Processing) or large-scale model development
- Knowledge of:
- MLOps
- CI/CD pipelines
- Production-level data science workflows
- Prior work in:
- Data annotation
- Data quality
- Evaluation systems
Why Join Us
- Work directly with industry-leading AI research labs on truly frontier problems
- Fully remote and flexible—work on your own schedule
- Enjoy freelance autonomy with intellectually stimulating work
- Engage hands-on with the most advanced language models being built today
- Potential for ongoing work and contract renewals as new projects launch
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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