Data Scientist (Masters)

Alignerr; Cambridge; On-site; GBP 83,000 - 138,000; Part time

Job summary

Alignerr is seeking Masters- or PhD-level Data Scientists to challenge and improve cutting-edge AI models. You will design hard problems, author gold-standard solutions, and audit AI outputs with a deep understanding of ML, statistics, and data engineering.

This is a fully remote, flexible hourly contract with 10–40 hours per week. You should be proficient in Python, R, or SQL; familiar with Scikit-Learn, PyTorch, and TensorFlow; and able to clearly communicate complex results in writing.

Qualifications

• Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science or a quantitatively focused field.
• Strong foundation in supervised and unsupervised learning, deep learning, and statistical modeling.
• Comfortable with Python, R, or SQL and standard data science libraries and frameworks.

Responsibilities

• Design Advanced Challenges — Craft complex, domain‑rich data science problems spanning hyperparameter optimization, Bayesian inference, cross‑validation strategies, dimensionality reduction, and more
• Author Ground‑Truth Solutions — Build rigorous, step‑by‑step technical solutions — Python/R scripts, SQL queries, mathematical derivations — that serve as definitive golden responses for model training
• Audit AI‑Generated Code — Evaluate AI outputs using libraries like Scikit‑Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
• Identify Reasoning Failures — Catch subtle flaws in AI logic — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that sharpens model reasoning
• Work Independently — Complete task‑based assignments on your own schedule, fully asynchronously

Skills

Python

R

SQL

Statistics

Deep learning

Bayesian inference

Cross-validation

Dimensionality reduction

Education

Masters or PhD in Data Science or related field

Tools

Scikit-Learn

PyTorch

TensorFlow

Job description

Data Scientist (Masters) — AI Data Trainer

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, and more
• Author Ground‑Truth Solutions — Build rigorous, step‑by‑step technical solutions — Python/R scripts, SQL queries, mathematical derivations — that serve as definitive "golden responses" for model training
• Audit AI‑Generated Code — Evaluate AI outputs using libraries like Scikit‑Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
• Identify Reasoning Failures — Catch subtle flaws in AI logic — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that sharpens model reasoning
• Work Independently — Complete task‑based assignments on your own schedule, fully asynchronously

Who You Are

• Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a heavily quantitative field
• Strong foundational command of supervised and unsupervised learning, deep learning, and statistical modeling
• Comfortable with Python, R, or SQL and standard data science libraries and frameworks
• Able to communicate complex algorithmic concepts and statistical results clearly in writing
• Naturally detail‑oriented — you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
• No prior AI or data annotation experience required

Nice to Have

• Familiarity with big data technologies like Spark or Hadoop
• Experience with NLP or large‑scale model development
• Background in MLOps, CI/CD pipelines, or production‑level data science workflows
• Prior work in data annotation, data quality, or evaluation systems

Why Join Us

• Work directly with industry‑leading AI research labs on genuinely frontier problems
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with meaningful, 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