Data and Analytics Support

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

We are seeking a detail-oriented and analytical Data & Analytics Support Contractor to support the assessment of integrity, reliability, and future-state requirements for PG reporting.

In this role, you will acquire and prepare data from complex operational and reporting platforms, perform reconciliations and targeted testing, analyze policy- and plan-level trends, validate effective dates and mappings, and translate technical findings into clear, decision-ready insights for cross-functional business and executive stakeholders.

You will partner closely with PG Reporting, Business, Technology, Operations, Workforce, Risk, Control, and Quality teams to distinguish isolated data anomalies from systemic reporting risks, while building traceable analysis, reusable calculation logic, and clear documentation that transitions to long-term owners.

Key Responsibilities

Data Discovery & Preparation

• Partner with assessment leads and subject-matter experts to convert business questions, policy requirements, and reporting risks into executable analysis plans.
• Identify, extract, combine, and prepare data from VQ inventories, Atlas records, dashboards, reconciliation files, source systems, volume reports, and prior issue documentation.
• Document data availability, ownership, business definitions, lineage, quality considerations, assumptions, and limitations.
• Evaluate data completeness, accuracy, consistency, lineage, timeliness, and fitness for purpose across primary operational and reporting systems.
• Perform multi-source reconciliations across source data, policy-to-VQ mappings, customer eligibility, effective dates, operational reports, client dashboards, and executive reporting.
• Design and execute targeted sampling to reproduce key metrics, validate corrected records, and confirm remediation effectiveness.
• Evaluate new, modified, consolidated, and sunset VQs to assess impacts on mappings, metrics, customer populations, and downstream reporting.

Trend Analysis & Risk Identification

• Analyze plan-level contact volumes and performance trends against historical baselines (MoM and YoY) to identify unusual shifts, outliers, and potential routing or reporting anomalies.
• Quantify the scope, severity, and business impact of findings, establishing clear assumptions and documenting unresolved gaps.
• Prioritize analytical efforts based on materiality, customer impact, risk recurrence, and executive decision value.

Reporting, Recommendations & Operationalization

• Translate complex dataset findings into concise visualizations, executive summaries, and decision-ready recommendations.
• Build repeatable analytical routines, SQL queries, calculation logic, metric definitions, monitoring thresholds, and data quality checks.
• Support evaluations of future-state source options, data models, reporting architecture, automation opportunities, and policy-specific attribution models.
• Maintain complete, organized analysis files, validation evidence, source-to-report lineage, and supporting documentation.
• Support post-assessment implementation activities (data remediation, dashboard development, user acceptance testing, and production monitoring) as work advances.

Qualifications Required:

• Education: Bachelor’s degree in Analytics, Data Science, Information Systems, Business, Finance, Operations, or equivalent practical experience.
• Experience: 5+ years of experience in data analysis, business intelligence, reporting, data quality, or operational analytics.
• Reconciliation Expertise: Proven background in reconciling complex, multi-source datasets and pinpointing root causes of reporting variances.
• Technical Proficiency: Strong expertise in SQL and advanced Excel; experience with enterprise BI and visualization platforms like Power BI or Tableau.
• Analytics Foundation: Demonstrated experience defining metrics, writing calculation logic, validating effective dates/mappings, and testing reporting outputs.
• Problem-Solving & Communication: Exceptional analytical judgment with the ability to structure ambiguous queries; excellent written and verbal communication skills to present technical findings to non-technical stakeholders.
• Cross-Functional Collaboration: Proven track record of working effectively across business, technology, operations, risk, and control teams under tight deadlines.

Preferred:

• Background in healthcare, pharmacy, contact-center, customer service, or regulated operational reporting environments.
• Working knowledge of data lineage, master/reference data management, single-source-of-truth design, governance, and data quality controls.
• Experience analyzing routing, queue, vendor, contact-volume, eligibility, or policy-level data structures.
• Familiarity with advanced analytics tools such as Python, R, Alteryx, Databricks, or cloud data platforms.