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Remote AI Data Trainer – Data Scientist (Masters)

Alignerr · Oxford

Nuevo Remote
Contract Remote 🇬🇧 English
Python SQL Scikit-Learn PyTorch TensorFlow Spark Hadoop

Descripcion del puesto

About the role

We are seeking a Data Scientist with a Master’s or PhD to design, evaluate, and improve cutting‑edge AI models. This fully remote, flexible contract position lets you apply advanced machine‑learning expertise to create challenging data‑science problems and refine model reasoning.

Key responsibilities

  • Design complex, domain‑specific challenges involving hyper‑parameter optimization, Bayesian inference, cross‑validation, and dimensionality reduction.
  • Author rigorous ground‑truth solutions using Python/R scripts, SQL queries, and mathematical derivations.
  • Audit AI‑generated code for technical accuracy, efficiency, and correctness using libraries such as Scikit‑Learn, PyTorch, and TensorFlow.
  • Identify logical failures in model outputs (e.g., data leakage, over‑fitting) and provide structured feedback.
  • Document failure modes across neural networks, statistical models, and data‑engineering pipelines.

Required profile

  • Pursuing or holding a Master’s or PhD in Data Science, Statistics, Computer Science, or a quantitative field.
  • Strong foundation in supervised/unsupervised learning, deep learning, and big‑data technologies.
  • Excellent written communication of algorithmic concepts and statistical findings.
  • Detail‑oriented with a keen eye for errors in code, mathematics, and statistics.

Required skills

  • Python
  • R
  • SQL
  • Scikit‑Learn
  • PyTorch
  • TensorFlow
  • Apache Spark
  • Hadoop

What we offer

  • Fully remote, asynchronous work schedule (10–40 hours/week).
  • Freelance autonomy with technically challenging projects.
  • Opportunity to work directly with industry‑leading large language models.
  • Potential for ongoing contracts as new AI projects launch.

Questions fréquentes

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Le contrat proposé est un Contract basé à Oxford.

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Publicado hace 2 horas

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Alignerr

Oxford