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AI Trainer, Data Science

Role overview

Qualifications

  • Fluency in English (native or bilingual level)
  • 2+ years of professional applied data science experience, in industry or research
  • Working proficiency in Python and/or SQL, with the ability to write, debug, and explain your own analysis code
  • A current, in progress, or completed Bachelor's in a quantitative field is preferred

Responsibilities

  • Design challenging, realistic data science tasks from your own practice
  • Run those tasks through frontier AI models and judge the output against your professional standard
  • Compare two model outputs on identical prompts and files, decide which performed better, and document where each fell short
  • Write detailed grading rubrics and tests that define what a correct deliverable must contain, and explain why a response passes or fails

Key facts

Hard skills

Other skills

  • Communication
  • Problem Solving

About the company

Brunel logo

Brunel

Staffing & Recruiting

Founded in 1975, we are a global specialist delivering customised project and workforce solutions to drive sustainable industry transformations through technology and talent. With 120+ offices and a powerful network of more than 12,000 specialists around the world, we deliver Project and Consulting Solutions, Workforce Solutions and Global Mobility Solutions that transform global projects in Renewables, Conventional Energy, Mining, Life Sciences, Future Mobility, Industrials & Technology and many other sectors.

Company details

Company typeXLarge
IndustryStaffing & Recruiting
Company size10001

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Job description

Brunel is partnering with DataAnnotation to connect experienced Data Scientists with an innovative AI training program. This opportunity brings together hands-on data science expertise and artificial intelligence to help evaluate and improve how AI models handle real data science work. Selected experts will contribute their knowledge to the development of high-quality, technically accurate AI systems.

This opportunity is designed for practicing data scientists who take analyses from messy data to a defensible conclusion. It covers product and business analytics, applied machine learning, statistics and experimentation, forecasting, analytics engineering, and applied NLP or computer vision.

Engagement Details

Engagement
Fully remote, project-based work with a flexible schedule. The minimum is 10 hours per week with no weekly maximum, and full-time hours are available.
Pay rate
$40–$125 USD/hour, paid via PayPal
Location
United Kingdom, Ireland, and Australia/New Zealand, United States, Canada.
First step
Skills assessment (2–4 hours)

Responsibilities:

  • Design challenging, realistic data science tasks from your own practice: an exploratory analysis of a messy dataset, an A/B test design and readout, or a model with proper validation
  • Run those tasks through frontier AI models and judge the output against your professional standard
  • Compare two model outputs on identical prompts and files, decide which performed better, and document where each fell short
  • Write detailed grading rubrics and tests that define what a correct deliverable must contain, and explain why a response passes or fails
  • Flag concrete failures with evidence: leakage, confounding, wrong joins, misapplied tests, code that runs but doesn't do what was asked, fabricated or ignored data, and off-brief interpretation
  • Contribute across analytics, machine learning, experimentation, and data engineering, and review and refine tasks built by other experts

Qualifications:

  • Fluency in English (native or bilingual level)
  • 2+ years of professional applied data science experience, in industry or research
  • Working proficiency in Python and/or SQL, with the ability to write, debug, and explain your own analysis code
  • Experience owning a multi-step analysis end to end, from raw data through modeling and interpretation to a decision
  • The ability to judge whether a result is real, and to explain why an answer is wrong, not only that it is
  • Working comfort with AI tools, or the ability to pick them up quickly
  • A current, in progress, or completed Bachelor's in a quantitative field is preferred


Note: Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. Only applicants in Australia, Canada, Ireland, New Zealand, the United Kingdom, and the United States will be considered for this role. This is an independent contractor position.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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