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Completed research & data-analysis case study

Pakistan analyst job market and skills demand

A stratified analysis of 24 public Pakistan job advertisements: eight Research, eight Data and eight Quality roles. The study maps role types, codes recurring skills, compares role-family profiles and converts the findings into a practical learning priority.

Observed27 July 2026
Sample24 job advertisements
MethodsSkill coding & frequency analysis
ToolsPublic research & spreadsheets
View full report Download dataset

Executive summary

The sampled market does not separate research, data and quality into completely isolated disciplines. All 24 postings required analytical thinking, reporting and communication. The main difference was the operating method: Research roles emphasized information gathering, market or competitor research and source documentation; Data roles emphasized cleaning, spreadsheets, reporting, dashboards and selected SQL; Quality roles emphasized validation, audit, documentation and process improvement.

The sample was deliberately balanced across role families. It is suitable for skill comparison, but it is not an estimate of how many jobs exist in each category.

Research question

What Research, Data and Quality analyst roles are publicly visible in Pakistan, which skills recur, and which skills should a candidate with practical research and reporting-quality experience prioritize first?

Methodology

  • Defined Research, Data and Quality as the three target role families.
  • Selected eight public postings per family for a balanced 24-posting demonstration sample.
  • Recorded title, employer, location, role information and source URL.
  • Coded thirteen recurring skill categories as present or absent using visible evidence.
  • Calculated total and role-family frequencies.
  • Retained the complete coded dataset and source index in the downloadable workbook.

Overall skill demand

Horizontal bar chart showing skill demand across 24 sampled Pakistan analyst roles
SkillPostingsShareInterpretation
Reporting / presentation24 of 24100%Universal across the sample.
Analytical / critical thinking24 of 24100%Universal across the sample.
Communication / stakeholder work24 of 24100%Analysis must be explained, not only produced.
Documentation / traceability20 of 2483%Especially visible in Research and Quality roles.
Data cleaning / validation17 of 2471%Central to Data roles and highly visible in Quality.
Excel / Google Sheets16 of 2467%The most accessible technical tool requirement.
Quality assurance / audit14 of 2458%Also common in operational Data roles.
SQL3 of 2413%Important in selected Data and Data Quality roles.
Python / scripting1 of 244%Desirable in one sampled posting, not universal.

Role-family skill profile

Grouped bar chart comparing Research, Data and Quality skill profiles

Research roles

All eight required research or information gathering; six involved market, competitor or industry research; seven required documentation or traceability; and all required reporting, analysis and communication.

Data roles

All eight involved cleaning or validation and reporting. Seven named Excel or Google Sheets, five involved BI or dashboards, two explicitly required SQL, and one listed Python as desirable.

Quality roles

All eight involved quality assurance or audit and documentation; seven involved data validation and process improvement; six included Excel or MS Office.

Candidate learning priority

  1. Research method and decision writing: defined questions, source logs, synthesis, limitations and recommendations.
  2. Excel / Google Sheets: formulas, pivots, lookups, cleaning, validation and charting.
  3. Data cleaning and validation: duplicate handling, standardization, completeness and traceability.
  4. Quality audit, RCA and CAPA: measurable criteria, defect classification and effectiveness checks.
  5. Basic SQL: SELECT, WHERE, GROUP BY, JOIN and reconciliation queries after initial job readiness.
  6. BI literacy: KPI definitions, dashboard interpretation and Power BI fundamentals.

Limitations

  • The sample is stratified and does not estimate role-family market share.
  • Job postings can change, expire or be duplicated across platforms.
  • Skill coding uses visible wording and may undercount implied requirements.
  • Search-result pages sometimes provide only partial job descriptions.

Selected public sources