Data Scientist (Masters)
Posted Today by Alignerr
Negotiable
Undetermined
Remote
London, England, United Kingdom
Summary: The Data Scientist (Masters) role involves leveraging advanced knowledge in machine learning and data engineering to develop and evaluate AI models. The position requires designing complex data science challenges, authoring technical solutions, and auditing AI-generated code to enhance AI reasoning. This is a fully remote, flexible contract position that does not require prior AI industry experience but demands strong analytical skills and domain expertise.
Key Responsibilities:
- Design Advanced Challenges — Create expert-level 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 definitive reference answers
- Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
- Sharpen AI Reasoning — Identify logical failures in AI responses — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that directly improves model reasoning
Key Skills:
- Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- Strong foundational knowledge across supervised and unsupervised learning, deep learning, big data technologies (Spark, Hadoop), or NLP
- Able to communicate complex algorithmic concepts and statistical results clearly and precisely in writing
- Detail-oriented — you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
- Self-motivated and comfortable working independently on an async schedule
- No prior AI or data annotation experience required
- Experience with data annotation, data quality systems, or model evaluation (nice to have)
- Familiarity with production-level data science workflows — MLOps, CI/CD pipelines for models (nice to have)
- Exposure to multiple programming languages and statistical environments (nice to have)
Salary (Rate): £32.00 hourly
City: London
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
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 thinks and reasons? We're looking for data scientists with advanced training to help build and stress-test cutting-edge AI models. You'll design the kinds of complex, expert-level challenges that push AI systems to their limits — and when they fail, you'll document exactly why, so we can make them better. This is a fully remote, flexible contract role. No prior AI industry experience required — just serious domain 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 — Create expert-level 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 definitive reference answers
- Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
- Sharpen AI Reasoning — Identify logical failures in AI responses — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that directly improves model reasoning
Who You Are
- Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- Strong foundational knowledge across supervised and unsupervised learning, deep learning, big data technologies (Spark, Hadoop), or NLP
- Able to communicate complex algorithmic concepts and statistical results clearly and precisely in writing
- Detail-oriented — you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
- Self-motivated and comfortable working independently on an async schedule
- No prior AI or data annotation experience required
Nice to Have
- Experience with data annotation, data quality systems, or model evaluation
- Familiarity with production-level data science workflows — MLOps, CI/CD pipelines for models
- Exposure to multiple programming languages and statistical environments
Why Join Us
- Work directly alongside industry-leading AI research labs on genuinely frontier technology
- Fully remote and asynchronous — work when and where it suits you
- Freelance autonomy with meaningful, intellectually stimulating work
- High-impact role where your expertise shapes how advanced AI understands data science
- Potential for ongoing contracts and expanded project opportunities as new work launches