Joins a talent pool for future projects that grade data science work and AI-generated analyses, with no current opening. Suits data scientists with leading-technology or quant-firm experience who take calibration feedback well.
About the role
This role is for one of our clients
Compensation: $100-$150 per hour
We are 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.
Requirements
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.
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
- Comfort receiving feedback and calibrating judgment against established standards
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