Senior Data Scientist (Remote | $245–$280/hr)

Job summary

Evaluate AI-generated solutions and create expert-level prompts, datasets, evaluation tasks, and reference solutions across data science, statistics, machine learning, and quantitative reasoning. Review analytical methods for accuracy, identify errors and weaknesses, and provide clear feedback and recommendations to improve AI performance.

Job details

Data Scientist Position: Data Scientist Type: Contractor Compensation: $245–$280/hour Location: Remote About the Opportunity We are seeking experienced Data Scientists and Quantitative Professionals to contribute to projects focused on improving how advanced AI systems reason about data, statistics, machine learning, experimentation, and quantitative analysis. In this role, you will apply your expertise to evaluate AI-generated solutions, develop challenging quantitative tasks, and provide expert feedback that helps improve model performance. The work involves assessing statistical reasoning, machine learning methodologies, experimental design, data analysis techniques, and quantitative problem-solving approaches. This opportunity is ideal for professionals with strong backgrounds in data science, machine learning, analytics, statistics, quantitative research, or related fields. No prior AI experience is required. Key Responsibilities Evaluate AI-generated responses involving data science, machine learning, statistics, and quantitative reasoning. Create expert-level prompts, datasets, evaluation tasks, and reference solutions. Review statistical analyses, machine learning workflows, and experimental methodologies for accuracy and rigor. Identify flawed assumptions, methodological errors, statistical mistakes, and weaknesses in quantitative reasoning. Assess the quality, correctness, and completeness of analytical solutions. Provide structured feedback and detailed explanations to support model improvement. Develop realistic scenarios involving data analysis, predictive modeling, experimentation, and statistical inference. Document findings and recommendations clearly and accurately. Contribute domain expertise to improve AI performance across quantitative disciplines. Required Qualifications Strong expertise in data science, statistics, machine learning, analytics, or a related quantitative field. Proficiency in Python and common data science libraries such as Pandas, NumPy, Scikit-learn, or similar tools. Strong understanding of statistical analysis, hypothesis testing, experimentation, and data modeling. Experience working with large datasets and quantitative problem-solving. Ability to identify methodological weaknesses and analytical errors. Excellent written communication skills for explaining technical concepts clearly. Strong analytical thinking and attention to detail. Ability to work independently in a remote environment. Preferred Qualifications At least one year of experience working at a leading technology, finance, research, or data-driven organization. Experience in machine learning model development, experimentation, or quantitative research. Background in predictive analytics, statistical modeling, causal inference, or applied machine learning. Experience designing experiments and evaluating model performance. Familiarity with AI systems, model evaluation, or data-centric AI workflows. Based in an English-speaking country. Strong ability to communicate complex quantitative concepts to technical and non-technical audiences. Compensation $245–$280/hour Remote contract engagement Flexible schedule Project-based work Additional Details Fully remote opportunity. 100 openings available. Flexible workload with no fixed schedule. Applications reviewed on a rolling basis. No prior AI experience required. Work focuses on evaluating and improving AI capabilities in statistics, machine learning, experimentation, and quantitative reasoning.

What you’ll do

Evaluate AI-generated solutions and create expert-level prompts, datasets, evaluation tasks, and reference solutions across data science, statistics, machine learning, and quantitative reasoning. Review analytical methods for accuracy, identify errors and weaknesses, and provide clear feedback and recommendations to improve AI performance.

Requirements

Requires strong expertise in data science or a related quantitative field, proficiency in Python and common data science libraries, and a solid understanding of statistics, experimentation, and data modeling. Candidates should have experience with large datasets, strong analytical and written communication skills, and the ability to work independently; relevant industry experience and AI evaluation familiarity are preferred.

Listed skills

• Machine learning · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Science
• Statistics
• Machine Learning
• Python
• Pandas
• NumPy
• Scikit-Learn
• Statistical Analysis
• Hypothesis Testing
• Experimental Design
• Data Modeling
• Quantitative Analysis
• Predictive Analytics
• Causal Inference
• Model Evaluation
• Technical Communication

Job areas

• Data & Analytics
• Technology
• Science & Research
• Software

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