Statistician

What you'll do

This ad is about the unglamorous part of statistics that takes most of the time in real work, with little advanced modelling: getting dirty data into shape, running sound basic analyses, and explaining them plainly. That is the workflow the customer wants an AI system to learn from.

The listed work:

• Cleaning, preprocessing and structuring messy datasets in R, Python, SAS or Stata
• Running and documenting descriptive and inferential analyses (hypothesis tests, regression) to find trends and patterns
• Building clear visualisations that support model development
• Annotating, labelling or enriching datasets to improve AI training data
• Writing concise summaries of methods and results for non-technical readers
• Flagging data quality problems and documenting how you handled incomplete or dirty data
• Working asynchronously with project stakeholders to resolve ambiguities

Documenting why you dropped, imputed or recoded something is probably the most useful output here, because models are poor at that judgement.

Who fits

• An MS or PhD in statistics, data science, mathematics, biostatistics or a related quantitative field
• Real experience cleaning messy data in R, Python, SAS or Stata
• Solid descriptive and inferential statistics, including hypothesis testing and regression
• Strong Python or R for analysis, manipulation and visualisation
• Experience with large, unstructured or noisy data across domains
• The ability to explain findings clearly to technical and non-technical audiences

The listed skills say "basic" statistics, but the preferred qualifications ask for a graduate degree. Expect the bar to be set by the degree and by how well you communicate, not by the sophistication of the methods.

What it pays

$60–120/hour, micro1's published band. That is above micro1's Biostatistician listing at $60–100/hour. No compensation structure, weekly hours or duration is stated.

Worth knowing

Good:

• 50 openings, marked high demand
• A $60 floor for fundamentally practical work
• Any of R, Python, SAS or Stata is accepted for the cleaning work
• Rewards communication as much as technical depth
• No country restriction stated, and no AI experience needed

Less good:

• A 2x spread with no stated basis for placement
• No pay structure, hours or duration published
• Data cleaning at volume can be repetitive
• Contractor engagement: no benefits, no notice period, your own tax to manage
• The customer and domain of the data are not named

About this listing

Posted by micro1 on its own jobs portal and read on 24 September 2026. The band, the 50 openings and the qualifications are from the listing; the comparison with the biostatistician listing is ours. See micro1.