Micro1
Micro1Verified listing
RemoteHot

Data Analyst - Remote US Contractor

30–60/hr
Remote
Posted September 29, 2026
contract
30 openings
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Listing checked September 29, 2026 · pay as published by Micro1

Overview

micro1 is hiring Data Analysts to support a customer's data quality project. You will review datasets and task outputs, flag errors, and apply evaluation rubrics to help train next-generation AI systems. No AI background is needed. Your analytical skills and attention to detail are what matter. This is a remote contractor role open to US-based candidates.

What You'll Do7

  • 1Examine datasets and detailed task outputs to verify accuracy, completeness, and guideline compliance.
  • 2Spot and report inconsistencies, mistakes, and outputs that stray from provided instructions.
  • 3Use structured rubrics and evaluation criteria consistently across large data sets.
  • 4Make sound judgments and document your reasoning when guidelines are unclear or ambiguous.
  • 5Escalate recurring data issues or patterns for further analysis instead of handling them one by one.
  • 6Deliver clear written and verbal feedback that identifies problems and suggests fixes.
  • 7Maintain high accuracy while processing repetitive data review tasks in volume.

Requirements9

  • 13–5+ years of experience in data review, data quality, quality assurance, or analytical roles.
  • 2Proven track record of reviewing, validating, and critiquing data or deliverables against explicit criteria.
  • 3Strong ability to follow detailed written instructions and apply complex evaluation rubrics with precision.
  • 4Comfort with ambiguity, including making justifiable decisions when guidelines are incomplete.
  • 5Advanced attention to detail and error-spotting skills across repetitive or high-volume work.
  • 6Solid written and verbal communication skills for documenting findings and giving feedback.
  • 7Baseline fluency with spreadsheets (sorting, filtering, simple formulas).
  • 8SQL or hands-on data querying is a plus.
  • 9Experience with data annotation, labeling, or rubric-based evaluation is advantageous.

Who Should Apply

This role suits someone with 3–5+ years in data review, quality assurance, or analytical work who enjoys applying structured criteria to large datasets. You should be comfortable making judgment calls when instructions are vague and have a sharp eye for errors in repetitive tasks. Candidates who struggle with ambiguity or dislike high-volume, detail-oriented review work may find this less suitable. A common reason applicants get rejected is failing to show how they have applied complex rubrics or handled ambiguous guidelines in past roles. Another is not demonstrating the ability to spot errors consistently across large datasets.

Salary Insight

The pay range is $30 to $60 per hour, as stated in the job posting. Final rate may depend on your experience and location.

Pay and demand for Data Engineering roles

Aggregated

Typical pay

$78/hour

This role

$30–$60/hr

Most Data Engineering roles pay $50–$97 per hour. This role's pay sits below that range.

Based on 180 similar roles that publish pay · 31 publish only a top rate; those count at the rate they gave

Typical rangeMedian payThis role

Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.

Live similar roles
247
Listed in last 30 days
159
Remote
92%

Hiring most right now: micro1 (100) · Turing (41) · Mercor (24)

Most requested skills · share of roles

  • python
    31%
  • excel
    12%
  • sql
    11%
  • business analysis
    11%

Figures from Data Engineering roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.

Compare your resume against these roles

Location

TypeRemote
LocationRemote
This is a remote position

Compensation

$30–60/hr

Required Skills

Data AnalysisData ReviewAttention to detailHandling ambiguityError spotting

Application Tip

In your application, highlight specific examples where you applied detailed rubrics or evaluation criteria to large datasets. Quantify your results, such as the volume of data reviewed or error rates reduced. Mention any experience with data annotation or SQL, as these are preferred qualifications.

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