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Mercor is building a network of experienced data scientists for potential future projects with leading AI research organizations. These projects may focus on evaluating how effectively AI systems perform real-world data science work. There is no immediate project opening, but qualified applicants may be contacted as relevant opportunities become available. ### 2\. Potential Responsibilities Future projects may involve: - Designing precise, task-specific grading criteria for data science deliverables, including exploratory data analyses, statistical modeling work, machine learning pipelines, experimentation and A/B test write-ups, feature engineering, and technical reports or notebooks - Evaluating AI-generated or human-created work against established criteria - Providing detailed written justifications for evaluations and scores - Applying consistent, evidence-based judgment so that assessments are reproducible and defensible - Incorporating structured feedback from senior reviewers and iterating on submitted work Specific responsibilities will vary depending on the project. ### 3\. Ideal Qualifications - 1+ years of professional data science experience - Experience at a leading technology, research, or quantitative firm (such as top FAANG, AI labs, top-tier quant funds, or equivalent) - Strong command of Python, SQL, statistical modeling, machine learning, experimentation and causal inference, and translating messy real-world data into rigorous analyses - Exceptional written communication skills, including the ability to convey technical findings clearly - A detail-oriented and consistent approach to evaluating complex work - Comfort receiving feedback and calibrating judgment against established standards