Data & Analytics Support Specialist

ibex; Karachi Division; On-site; PKR 1,674,000 - 2,120,000; Full time

Job summary

ibex seeks a detail-oriented Data & Analytics Support Contractor to help assess integrity, reliability, and future-state requirements for PG reporting. You will acquire and prepare data from complex sources, perform reconciliations, analyze trends, and translate findings into decision-ready insights for cross-functional stakeholders.

Collaborating with PG Reporting, Business, Technology, Operations, Workforce, Risk, and Quality teams, you’ll distinguish data anomalies from systemic risks while

Qualifications

• Bachelor’s degree in analytics, data science, information systems, or related field.
• 5+ years in data analysis, BI, reporting, or operational analytics.
• Reconciliation of multi-source datasets to find root causes of variances.
• SQL and advanced Excel; experience with Power BI or Tableau.
• Experience defining metrics, calculation logic, and validating dates/mappings.
• Strong communication to present findings to non-technical stakeholders.

Responsibilities

• Convert business questions, policy requirements, and reporting risks into executable analysis plans.
• Extract, combine, and prepare data from multiple sources and platforms.
• Document data ownership, lineage, and quality considerations.
• Perform multi-source reconciliations and sampling to validate metrics and remediation.
• Translate findings into visualizations and recommendations for executives.

Skills

SQL

Excel

Communication

Cross-functional collab

Education

Bachelor's degree

Tools

Power BI

Tableau

Job description

ibex seeks a detail-oriented Data & Analytics Support Contractor to help assess integrity, reliability, and future-state requirements for PG reporting. You will acquire and prepare data from complex sources, perform reconciliations, analyze trends, and translate findings into decision-ready insights for cross-functional stakeholders.

Collaborating with PG Reporting, Business, Technology, Operations, Workforce, Risk, and Quality teams, you’ll distinguish data anomalies from systemic risks while