Excel Quality Assurance Lead (QAL)

Job Summary

As an Excel Quality Assurance Lead (QAL), you will oversee quality, consistency, and contributor performance across Excel and spreadsheet-focused AI training projects.

This role involves reviewing AI-generated formulas, spreadsheet workflows, financial models, analytical explanations, and QA outputs to ensure accuracy, clarity, reproducibility, and compliance with project standards.

Your work will directly contribute to improving advanced AI systems by ensuring spreadsheet training data is technically correct, practical, clearly explained, and aligned with client expectations.

Key Responsibilities

Quality Monitoring

• Spot-check spreadsheet and Excel-related tasks
• Identify recurring quality issues and process gaps
• Provide actionable written feedback and escalate critical concerns

Spreadsheet Review

• Review and evaluate:

  • Excel formulas
  • Spreadsheet workflows
  • Financial models
  • Data-cleaning processes
  • Pivot tables
  • Charts and visualizations
  • Analytical explanations

• Assess work for:

  • Formula correctness
  • Spreadsheet logic
  • Data-analysis accuracy
  • Reproducibility
  • Model structure
  • Instruction adherence

Trainer & QA Communication

• Communicate updates regarding:
  • Guidelines
  • Workflow changes
  • Spreadsheet standards
  • Quality expectations

Contributor Support

• Answer questions involving:
  • Formulas
  • Cell references
  • Lookup functions
  • Dynamic arrays
  • Pivot tables
  • Power Query
  • Modeling assumptions
  • Rubric interpretation

Activation Management

• Follow up with inactive contributors
• Track engagement and participation
• Report contributor availability concerns

Documentation & Onboarding

• Create and maintain:

  • Style guides
  • Documentation
  • FAQs
  • Examples
  • Calibration tasks
  • Onboarding materials

• Conduct onboarding and training sessions for contributors

Spreadsheet Quality Review

• Identify and flag:
  • Incorrect formulas
  • Circular references
  • Fragile spreadsheet logic
  • Poor modeling assumptions
  • Missing edge cases
  • Misleading charts
  • Risky financial or business assumptions

Process Improvement

• Improve QA workflows and spreadsheet review processes
• Identify recurring quality gaps and implement corrective actions

Required Qualifications

• Bachelor's or Master's degree in:
  • Finance
  • Accounting
  • Business
  • Data Analytics
  • Economics
  • Statistics
  • Operations
  • Information Systems

or equivalent professional experience.

• Strong English communication skills

• Minimum 3 years of experience using Excel for:

  • Financial modeling
  • Reporting
  • Business analysis
  • Accounting
  • Operations
  • Data analysis
  • Spreadsheet QA

• Strong understanding of:

  • Formulas and functions
  • Cell references
  • Lookup logic
  • Dynamic arrays
  • Pivot tables
  • Charts
  • Conditional formatting
  • Data validation
  • Spreadsheet modeling best practices

• Ability to identify:

  • Incorrect formulas
  • Broken references
  • Circular logic
  • Weak assumptions
  • Fragile spreadsheet models
  • Misleading visualizations

Preferred Qualifications

• Experience with:

  • XLOOKUP
  • INDEX/MATCH
  • SUMIFS
  • COUNTIFS
  • FILTER
  • SORT
  • UNIQUE
  • LET
  • LAMBDA

• Familiarity with:

  • Power Query
  • Power Pivot
  • VBA
  • Macros
  • Solver
  • Scenario modeling

• Experience leading:

  • Analysts
  • Finance teams
  • Trainers
  • Reviewers
  • QA teams

• Experience with:

  • AI training
  • Spreadsheet QA
  • LLM evaluation
  • Rubric-based review workflows

Why Join

• Help improve leading AI systems through spreadsheet and analytical quality assurance
• Flexible remote schedule
• Weekly payments
• Referral rewards and community incentives
• Access to future opportunities through SME Careers' expert network

Selection Process

1. AI Interview
2. Domain-Specific Assessment
3. Recruiter Interview

Important Note

There is currently no active project for this role. Qualified candidates will be added to the expert network and contacted when relevant opportunities become available.