Data Scientist Talent Network

Accountabilities:

• Design precise, task-specific grading criteria for data science deliverables, including exploratory data analyses, statistical modeling, machine learning pipelines, and A/B test analyses.
• Evaluate AI-generated and human-created data science work against established criteria to assess technical quality, accuracy, rigor, and consistency.
• Review analytical approaches, statistical assumptions, modeling methodologies, experiment design, and interpretation of results.
• Assess Python and SQL-based work for correctness, efficiency, reproducibility, and appropriate application to the underlying business or analytical problem.
• Provide detailed written justifications for evaluations and scores to ensure transparency, accountability, and reproducibility.
• Apply consistent, objective, and evidence-based judgment when evaluating complex technical work.
• Identify methodological weaknesses, data issues, incorrect assumptions, statistical errors, and opportunities for improvement.
• Assess machine learning workflows for appropriate model selection, validation, performance evaluation, and interpretation.
• Incorporate structured feedback from senior reviewers and iterate on submitted evaluations to continuously improve quality.
• Work independently and asynchronously while meeting deadlines and maintaining high standards of technical accuracy.

Requirements:

• 1+ year of professional data science experience with hands-on exposure to real-world analytical or machine learning projects.
• Experience working at a leading technology, research, quantitative, or data-driven organization is preferred.
• Strong command of Python and SQL, with practical experience in data analysis and manipulation.
• Strong knowledge of statistical modeling, machine learning, experimentation, and A/B testing methodologies.
• Ability to evaluate exploratory data analyses, statistical models, machine learning pipelines, and experimental results critically and objectively.
• Strong understanding of data quality, statistical assumptions, model validation, experiment design, and analytical best practices.
• Exceptional written communication skills, with the ability to clearly explain technical reasoning, findings, and evaluation decisions.
• Strong analytical and critical-thinking skills, with excellent attention to detail.
• Consistent and methodical approach to evaluating complex technical work.
• Comfortable receiving structured feedback and calibrating professional judgment against established evaluation standards.
• Ability to work independently in a remote, asynchronous environment while managing priorities and meeting deadlines.
• Experience with AI model evaluation, data labeling, benchmarking, human-data projects, or AI training is a plus.

Benefits:

• Competitive contract compensation: $100–$150 per hour.
• Fully remote opportunity, offering flexibility to work from your preferred location in India.
• Flexible, asynchronous working environment designed for experienced data science professionals.
• Opportunity to apply data science expertise to the development and evaluation of advanced AI systems.
• Direct contribution to improving the accuracy, reliability, and capabilities of AI-generated analytical work.
• Exposure to projects involving machine learning, statistical modeling, experimentation, and AI model evaluation.
• Opportunity to collaborate with senior reviewers and participate in structured technical calibration.
• Flexible contract engagement that allows you to contribute your expertise to impactful AI projects.