Data Science Expert - AI Content Specialist
Posted 1 week ago by Alignerr
Negotiable
Undetermined
Remote
London, England, United Kingdom
Summary: The Data Science Expert — AI Content Specialist role involves leveraging expertise in machine learning and data engineering to refine AI models by designing complex challenges and providing rigorous solutions. This fully remote contract position is ideal for data scientists and researchers seeking impactful work on a flexible schedule. Responsibilities include auditing AI-generated code and identifying logical failures to enhance model performance. Candidates should possess strong quantitative skills and the ability to communicate complex concepts effectively.
Key Responsibilities:
- Design Advanced Challenges — Create complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Build Ground-Truth Solutions — Author rigorous, step-by-step technical responses including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive reference answers
- Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
- Refine AI Reasoning — Identify logical failures such as data leakage, overfitting, improper handling of class imbalance, or flawed statistical conclusions, and provide structured feedback to improve model behavior
Key Skills:
- Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative discipline
- Strong foundational knowledge in supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop)
- Able to communicate complex algorithmic and statistical concepts clearly in writing
- Meticulous attention to detail — you catch errors in code syntax, mathematical notation, and statistical logic
- No prior AI or annotation experience required
- Experience with data annotation, data quality, or model evaluation workflows (nice to have)
- Familiarity with production data science practices such as MLOps or CI/CD pipelines for models (nice to have)
- Background in academic research or technical writing (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 Science Expert — AI Content Specialist
About The Role
What if your expertise in machine learning, statistical modeling, and data engineering could directly shape the next generation of AI? We're looking for Data Science Experts to stress-test and refine advanced AI models — designing hard problems, building gold-standard solutions, and identifying exactly where AI reasoning breaks down. This is a fully remote, flexible contract role built for working data scientists, researchers, and advanced students who want meaningful, high-impact work on their own schedule.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Challenges — Create complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Build Ground-Truth Solutions — Author rigorous, step-by-step technical responses including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive reference answers
- Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
- Refine AI Reasoning — Identify logical failures such as data leakage, overfitting, improper handling of class imbalance, or flawed statistical conclusions, and provide structured feedback to improve model behavior
Who You Are
- Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative discipline
- Strong foundational knowledge in supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop)
- Able to communicate complex algorithmic and statistical concepts clearly in writing
- Meticulous attention to detail — you catch errors in code syntax, mathematical notation, and statistical logic
- No prior AI or annotation experience required
Nice to Have
- Experience with data annotation, data quality, or model evaluation workflows
- Familiarity with production data science practices such as MLOps or CI/CD pipelines for models
- Background in academic research or technical writing
Why Join Us
- Work directly with industry-leading AI research labs on cutting-edge language models
- Fully remote and async — work on your own schedule, from anywhere
- Freelance flexibility with consistent, meaningful task-based work
- High-autonomy contractor role with global reach
- Potential for ongoing work and contract extension as new AI projects launch