Data Scientist
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Job Description
Data Scientist evaluating AI-generated statistical and machine-learning work for 24-MAG’s consulting network. Reviewing analyses, developing rubrics, and delivering defensible technical feedback.
Responsibilities:
- Evaluate realistic data science deliverables produced by AI systems or human contributors
- Review exploratory data analyses, statistical models, machine learning pipelines, technical reports, Python, SQL, notebooks, and related analytical outputs
- Assess analytical correctness, methodology, completeness, practical usefulness, and whether conclusions are supported by available data
- Identify flawed assumptions, methodological weaknesses, and unsupported conclusions
- Develop precise, task-specific grading criteria and reproducible, defensible evaluation standards
- Review feature engineering, model selection, validation, interpretation, experimentation, A/B testing, and causal inference approaches
- Provide detailed written justification for evaluation scores and communicate technical findings to specialist and broader audiences
- Incorporate structured reviewer feedback and calibrate evaluations against established standards
- Maintain accuracy and consistency across complex review assignments
- Join a talent network for potential future advanced AI and data science consulting projects; no immediate project is currently available
Requirements:
- At least 1 year of professional data science experience
- Strong proficiency in Python and SQL
- Hands-on experience with statistical modelling and machine learning
- Experience designing or analysing experiments and A/B tests
- Familiarity with causal inference methods
- Ability to work effectively with messy, real-world datasets
- Strong analytical reasoning and attention to detail
- Excellent written communication skills
- Ability to explain technical conclusions clearly and precisely
- Comfort receiving feedback and calibrating professional judgment against established standards
- A degree in data science, statistics, computer science, mathematics, economics, engineering, or a related quantitative discipline may be highly relevant
- Advanced quantitative or machine learning training may strengthen an application
- Equivalent professional experience demonstrating strong data science expertise may also be considered
- Practical experience delivering rigorous real-world analysis is particularly valuable
- Nice to have: experience at a leading technology, AI research, quantitative finance, or research organisation
- Nice to have: advanced statistical experimentation and causal inference knowledge
- Nice to have: production machine learning workflows
- Nice to have: exploratory analysis across large or complex datasets
- Nice to have: technical notebooks or analytical reports
- Nice to have: reviewing or mentoring other data scientists
- Nice to have: AI evaluation, structured review, benchmarking, or human-data projects
Benefits:
- Potential future remote consulting opportunities
- Project-based opportunities
- Potential rates of $95–$145 per hour depending on expertise and individual project scope
- Flexible workload, duration, schedule, and responsibilities varying by project
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