AI Trainer, Data Science

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, * 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

• 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