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Data Analyst

micro1 · 100% remote · Contract · Posted

Pay
$50–60/hr
Location
Worldwide
Languages
English
Hours
Flexible
Openings
4
Level
Experienced
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Summary

Evaluate AI assistants in analytical workflows using cloud data warehouses. Verify figures with SQL, manage Snowflake test datasets and access, and grade outputs. Prior AI experience is not required.

What you'll do

  • Evaluate anomaly investigations, KPI reports, and data refreshes.
  • Verify AI-generated figures with independent SQL queries.
  • Check joins, filters, and time windows.
  • Maintain and reset seeded Snowflake datasets.
  • Manage warehouse roles, permissions, and access controls.
  • Configure and document platform connections and authentication.
  • Investigate and document product behavior.
  • Join calibration sessions for consistent grading.

Requirements

  • Preferred: at least 3 years as a data analyst or analytics engineer.
  • Advanced SQL skills and Snowflake expertise.
  • Ability to audit metrics and identify aggregation or logic errors.
  • Familiarity with Claude and ChatGPT connectors.
  • Knowledge of business and finance analytics and KPI reporting.
  • Experience managing database access, roles, grants, and authentication.
  • Working knowledge of common SaaS tools and AI analytics assistants.
  • Experience with rubric-based evaluation, QA, or data labeling and strong communication skills.

Skills

  • Reporting
  • SQL
  • Snowflake
  • QA

Full description

Role Title: Data Analyst


Role Type: Contractor


Location: Remote


micro1 is engaging Data Analysts to contribute expertise to a confidential client project focused on evaluating AI assistants in real-world analytical workflows leveraging cloud data warehouses. 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

  1. Execute structured evaluation tasks simulating typical analytical workflows (e.g., anomaly investigation, KPI reporting, data refreshes) using AI-powered solutions with cloud data warehouse connectivity.
  2. Independently verify AI-generated figures against source data by writing and running your own SQL queries, and assess the correctness of data joins, filters, and time windows.
  3. Maintain, reset, and manage seeded datasets within Snowflake, ensuring data integrity and correct answer states for test scenarios.
  4. Oversee warehouse roles, permissions, and access controls to facilitate secure and repeatable evaluation environments.
  5. Configure and document connectivity and authentication processes across multiple analytics and SaaS platforms.
  6. Investigate and document novel or undocumented product behavior encountered during workflow execution.
  7. Participate in calibration sessions with peers to ensure consistency and rigor when grading or scoring outputs.


Preferred Qualifications

  1. At least 3 years of hands-on experience as a data analyst or analytics engineer, with advanced SQL skills and expertise in Snowflake (warehouses, access control, query history).
  2. Demonstrated proficiency in auditing and reconciling reported metrics against raw data, with a keen eye for catching subtle aggregation or logic errors.
  3. Versed in using connectors across Claude and ChatGPT.
  4. Familiarity with business and finance analytics, including KPI definitions and reporting practices relevant to leadership or external stakeholders.
  5. Experience in administering database access, managing roles, grants, and integrating authentication/security protocols; OAuth or security-integration familiarity is advantageous.
  6. Working knowledge of common SaaS tools such as Slack, Google Workspace, or Microsoft 365 for sharing analytical outcomes.
  7. Prior experience using AI assistants for analytics, with a critical perspective on the accuracy of AI-generated SQL and outputs.
  8. Background in rubric-based evaluation, QA, or data labeling, with a meticulous approach and strong written and verbal communication skills.

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