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Statistician - AI Trainer

micro1 is selecting Statisticians to contribute expert knowledge to a customer project focused on advancing data-driven solutions. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

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Salary

$60 - $120 / hour

Department

Statistics & Data Analysis

Experience

3+ years

Responsibilities

Clean, preprocess, and structure complex and messy datasets using statistical software such as R, Python, SAS, or Stata.
Apply and document descriptive and inferential statistical analyses to uncover trends and patterns in real-world data.
Develop clear and compelling data visualizations to illustrate key findings and support model development.
Contribute expertise in dataset annotation, labeling, or enrichment to enhance the quality of AI model training datasets.
Draft concise, well-organized written summaries of methods, analyses, and results for non-technical audiences.
Collaborate asynchronously with project stakeholders to clarify requirements, resolve ambiguities, and improve deliverables through effective written and verbal communication.
Identify data quality issues, provide actionable recommendations, and document solutions for handling dirty or incomplete data.

Skills

Data Cleaning and PreparationDirty Data AnalysisDescriptive StatisticsInferential StatisticsStatistical AnalysisPythonRSASStataData VisualizationDataset AnnotationStatistical ReportingTechnical Communication

Requirements

Advanced degree (MS or PhD) in Statistics, Data Science, Mathematics, Biostatistics, or a related quantitative field.
Expertise in cleaning and preparing complex, messy datasets using R, Python, SAS, or Stata.
Proficiency in descriptive and inferential statistical techniques, including hypothesis testing and regression analysis.
Strong programming skills in Python or R for statistical analysis, data manipulation, and visualization.
Demonstrated ability to communicate complex findings to both non-technical and technical audiences with clarity and precision.
Experience working with large, unstructured, or noisy datasets across a variety of domains.
Excellent written and verbal communication skills, with a focus on detailed documentation and collaboration in remote environments.

Benefits

Remote contractor opportunity
Contribute statistical expertise to next-generation AI training
Work with real-world complex and messy datasets
Help improve AI model training through expert data analysis and annotation
Opportunity to influence data-driven AI development and evaluation

Statistician - AI Trainer

Responsibilities

Clean, preprocess, and structure complex and messy datasets using statistical software such as R, Python, SAS, or Stata.

Apply and document descriptive and inferential statistical analyses to uncover trends and patterns in real-world data.

Develop clear and compelling data visualizations to illustrate key findings and support model development.

Contribute expertise in dataset annotation, labeling, or enrichment to enhance the quality of AI model training datasets.

Draft concise, well-organized written summaries of methods, analyses, and results for non-technical audiences.

Collaborate asynchronously with project stakeholders to clarify requirements, resolve ambiguities, and improve deliverables through effective written and verbal communication.

Identify data quality issues, provide actionable recommendations, and document solutions for handling dirty or incomplete data.

Requirements

Advanced degree (MS or PhD) in Statistics, Data Science, Mathematics, Biostatistics, or a related quantitative field.

Expertise in cleaning and preparing complex, messy datasets using R, Python, SAS, or Stata.

Proficiency in descriptive and inferential statistical techniques, including hypothesis testing and regression analysis.

Strong programming skills in Python or R for statistical analysis, data manipulation, and visualization.

Demonstrated ability to communicate complex findings to both non-technical and technical audiences with clarity and precision.

Experience working with large, unstructured, or noisy datasets across a variety of domains.

Excellent written and verbal communication skills, with a focus on detailed documentation and collaboration in remote environments.