Data Science Expert - AI Content Specialist

Data Science Expert - AI Content Specialist

Posted Today by Alignerr

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Negotiable
Undetermined
Remote
Manchester, England, United Kingdom
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Apache Hadoop Artificial Intelligence Bayesian Inference Big Data Computer Science Continuous Integration and Continuous Delivery Data Engineering Data Quality Data Science Deep Learning Dimensionality Reduction External Auditing Machine Learning Probability And Statistics PyTorch (Machine Learning Library) Scheduling Scikit-learn (Machine Learning Library) SQL (Programming Language) Statistics Syntax TensorFlow Workflows

Summary: The Data Science Expert — AI Content Specialist role involves leveraging expertise in machine learning and data science to enhance AI systems. This fully remote position allows professionals to design complex data challenges, author solutions, and audit AI-generated code. Candidates will provide critical feedback to improve AI reasoning and outputs. The role is flexible, offering 10–40 hours of work per week.

Key Responsibilities:

  • Design Advanced Challenges covering topics like hyperparameter optimization and Bayesian inference.
  • Author Ground-Truth Solutions including Python/R scripts and SQL queries.
  • Audit AI-Generated Code for correctness and efficiency.
  • Refine Model Reasoning by identifying logical failures in AI outputs.

Key Skills:

  • Master's or PhD in Data Science, Statistics, Computer Science, or related field.
  • Strong expertise in supervised/unsupervised learning, deep learning, and big data technologies.
  • Ability to communicate complex concepts clearly in writing.
  • Detail-oriented in reviewing code syntax and statistical conclusions.
  • No prior AI or annotation experience required.

Salary (Rate): £32.00 hourly

City: Manchester

Country: United Kingdom

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Data Science Expert — AI Content Specialist

About The Role

What if your deep knowledge of machine learning, statistics, and data engineering could directly shape the intelligence of tomorrow's AI systems? We're looking for Data Science Experts to challenge, evaluate, and improve cutting-edge language models — exposing their blind spots and helping them reason more rigorously about complex technical problems. This is a fully remote, flexible contract role designed for data science professionals who want to do meaningful, intellectually stimulating work on their own schedule.

Organization: Alignerr

Type: Hourly Contract

Location: Remote

Commitment: 10–40 hours/week

What You'll Do

  • Design Advanced Challenges — Craft complex, domain-spanning data science problems covering topics like hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
  • Author Ground-Truth Solutions — Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive benchmarks for AI evaluation
  • Audit AI-Generated Code — Critically evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing them for correctness, efficiency, and technical soundness
  • Refine Model Reasoning — Identify logical failures in AI outputs — such as data leakage, overfitting, or mishandled class imbalance — and provide structured feedback that directly improves how these models think and respond

Who You Are

  • Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
  • Strong foundational expertise in core data science domains: supervised/unsupervised learning, deep learning, big data technologies (Spark, Hadoop), or NLP
  • Able to communicate complex algorithmic and statistical concepts clearly and precisely in writing
  • Exceptionally detail-oriented when reviewing code syntax, mathematical notation, and statistical conclusions
  • No prior AI or annotation experience required — your domain expertise is what matters

Nice to Have

  • Experience with data annotation, data quality assurance, or evaluation pipelines
  • Familiarity with production-level data science workflows such as MLOps or CI/CD for models
  • Background in academic research or technical writing

Why Join Us

  • Work directly on projects with the world's leading AI research labs and teams
  • Fully remote and asynchronous — work when and where it suits you
  • Freelance autonomy with the structure of meaningful, expert-level technical work
  • High-impact contributions: your feedback directly shapes the reasoning ability of advanced AI systems
  • Potential for ongoing work and contract extension as new projects launch
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