Statistician
micro1 · 100% remote · Contract · Posted
- Pay
- $60–120/hr
- Location
- Worldwide
- Languages
- English
- Hours
- Flexible
- Openings
- 50
- Level
- Expert
Summary
Remote contractor role applying statistical expertise to AI training. Work includes cleaning complex datasets, conducting statistical analyses, creating visualizations, annotating data, and explaining results to non-technical audiences.
What you'll do
- Clean and structure complex datasets.
- Apply and document descriptive and inferential analyses.
- Create visualizations of findings.
- Annotate, label, or enrich training datasets.
- Write summaries of methods and results.
- Clarify requirements with project stakeholders.
- Identify data quality issues and document solutions.
Requirements
- Preferred: MS or PhD in statistics or a related quantitative field.
- Expertise cleaning messy data with R, Python, SAS, or Stata.
- Proficiency in hypothesis testing, regression, and other basic statistical methods.
- Strong Python or R skills for analysis and visualization.
- Experience with large, unstructured, or noisy datasets.
- Ability to explain findings to technical and non-technical audiences.
- Clear written and verbal communication and detailed documentation.
Skills
- Data Cleaning and Preparation (Dirty Data)
- Basic Descriptive and Inferential Statistics
- Programming in Python or R for Analysis
- Data Visualization
- Communicating Findings to a Non-Technical Audience
Full description
Role Title: Statistician
Role Type: Contractor
Location: Remote
micro1 is selecting Statistician 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.
Scope of Work
- Clean, preprocess, and structure complex and messy datasets using advanced statistical software (such as R, Python, SAS, or Stata).
- Apply and document basic 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 a non-technical audience.
- Collaborate asynchronously with project stakeholders to clarify requirements, resolve ambiguities, and improve deliverables through effective written and verbal communication.
- Continuously identify data quality issues, provide actionable recommendations, and document solutions for handling dirty or incomplete data.
Preferred Qualifications
- Advanced degree (MS or PhD) in Statistics, Data Science, Mathematics, Biostatistics, or a related quantitative field.
- Expertise in cleaning and preparing complex, messy (“dirty”) datasets with R, Python, SAS, or Stata.
- Proficiency in basic 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 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.
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