Jobs · Analyst

Statistician

micro1 · NAMER · 1 wk ago
RemoteRemoteAnalystContract

About the role

micro1 is selecting a 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.

Responsibilities

  • 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.

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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