AlignerrCoding & software eval
Data Scientist (Masters)
up to $80/hr
About this role, in Alignerr's words
What if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason about data? We're looking for experienced data scientists to challenge, evaluate, and improve cutting-edge AI models — exposing their blind spots, correcting their logic, and building the ground-truth solutions that make them smarter.
What you'll do
- Design Advanced Challenges — Create complex, real-world data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive reference answers for AI training
- Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness
Show all 5 itemsHide the other 2 in What you'll do
- Identify Reasoning Failures — Catch logical errors in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that improves how models think
- Work Independently — Complete task-based assignments asynchronously on your own schedule
Candidate background
Who You Are
- Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with strong emphasis on data analysis
- Deeply fluent in core ML concepts — supervised/unsupervised learning, deep learning, probabilistic modeling, and statistical inference
- Comfortable working across big data technologies (Spark, Hadoop) and/or NLP frameworks
- Able to communicate complex algorithmic concepts and statistical results clearly in writing
- Precise and thorough — you catch errors in code syntax, mathematical notation, and statistical conclusions
- No prior AI training or annotation experience required
Nice to Have
Show all 3 itemsHide these 3 items in Nice to Have
- Experience with data annotation, data quality pipelines, or model evaluation systems
- Proficiency in production-level data science workflows — MLOps, CI/CD for models, or similar
- Background in academic research or technical writing
Quoted from selected sections of Alignerr's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Alignerr's words
Posted by Alignerr, reproduced here so you can judge the role before clicking. Original posting ↗
Data Scientist (Masters) — AI Data 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 about data? We're looking for experienced data scientists to challenge, evaluate, and improve cutting-edge AI models — exposing their blind spots, correcting their logic, and building the ground-truth solutions that make them smarter.
This is a fully remote, flexible contract role. No prior AI industry experience required — just deep, hands-on data science knowledge and the ability to communicate it with precision.
- Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week
What You'll Do
* Design Advanced Challenges — Create complex, real-world data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more * Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive reference answers for AI training * Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness * Identify Reasoning Failures — Catch logical errors in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that improves how models think * Work Independently — Complete task-based assignments asynchronously on your own schedule
Who You Are
* Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with strong emphasis on data analysis * Deeply fluent in core ML concepts — supervised/unsupervised learning, deep learning, probabilistic modeling, and statistical inference * Comfortable working across big data technologies (Spark, Hadoop) and/or NLP frameworks * Able to communicate complex algorithmic concepts and statistical results clearly in writing * Precise and thorough — you catch errors in code syntax, mathematical notation, and statistical conclusions * No prior AI training or annotation experience required
Nice to Have
* Experience with data annotation, data quality pipelines, or model evaluation systems * Proficiency in production-level data science workflows — MLOps, CI/CD for models, or similar * Background in academic research or technical writing
Why Join Us
* Work directly on cutting-edge AI projects alongside world-leading research labs * Fully remote and flexible — work when and where it suits you * Freelance autonomy with meaningful, intellectually stimulating work * Direct engagement with the most advanced large language models being built today * Potential for ongoing contracts and expanded project opportunities as new work launches
Working with AlignerrPay, getting started and work, from Alignerr's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Billed weekly, Monday to Sunday, with approved work paid by the following Friday, according to Labelbox's help center. Payment goes through Stripe Connect or PayPal depending on your location, with one provider per country. intercom.help/labelbox/en/articles/13600616-alignerr-paym..., alignerr.com/process
- Before your first paid task
- Sign up, apply, verify your identity, set up billing and onboard. Some jobs add a Zara AI interview or domain assessments. alignerr.com/process
- How much work
- Time to your first project depends on demand and your skills, and there is no minimum number of hours. alignerr.com/faqs
- Contract
- Independent contractor, under terms with ALIGNERR LLC. alignerr.com/faqs, alignerr.com/privacy
Read on the pages linked above on 24 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Coding & software eval roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Alignerr's posting. How we count.
Pay across the field: Coding & software eval
Across 393 roles in this field with a stated hourly rate in US dollars, on 14 platforms, the middle half pays $65 to $120 an hour at the top of the range, and the median is $95. This role's top rate, $80, is in the middle half. Of the 141 distinct rates we count, 49 are lower and 82 are higher.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr (this platform) | 136 | $50 to $400 · median $100 |
| micro1 | 46 | $35 to $350 · median $110 |
| Handshake AI | 43 | $47 to $125 · median $80 |
| Meridial (Invisible) | 34 | $22 to $150 · median $60 |
| Mercor | 33 | $60 to $200 · median $105 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 27 Aug 2026, and still on Alignerr's list when we last read it on 13 Oct 2026.
- The listed pay has not changed since then.
- Posted by Alignerr
- First seen by AIPayList
- Last seen live
- Listing ID
- 065cb980-51f4-4a93-82f2-df8a33b63c16
Pay as the source states it: “$40-80/hr”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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