Expert Service Performance & Analytics

Grade Level: L2 Location: Islamabad Last Date to Apply: 11th August 2026

What is Expert Service Performance & Analytics? JazzCash is moving customer servicing from a reactive support model to an intelligence-led operation, and onward to AI-assisted and eventually agentic servicing. This role is the measurement layer that makes that shift possible and provable. The Expert Service Performance & Analytics owns the analysis behind how JazzCash serves its customers: why contacts happen, where journeys break, what deflection and containment we are actually achieving, and what leadership should do about it. The role produces the numbers that appear in weekly CEO and ELT reporting, and establishes the baseline against which the AI servicing programme is measured.

What does Expert Service Performance & Analytics do? This role sits within Customer Operations and works across the full servicing estate. Its boundaries with Technology and with the Experience Transformation & Innovation function are deliberate and are set out below. In scope: •     Analysis, insight and recommendation across service performance, complaint drivers and customer journeys. •     Operational and executive reporting, dashboards and scorecards built on data available through the enterprise data platform. •     Forecasting of contact demand and capacity analytics, including modelling for disbursement-cycle surges. •     Measurement of self-service, IVR, bot and WhatsApp deflection, containment and quality — including the baseline for the AI servicing programme. •     Root-cause analysis of contact and complaint drivers, service incidents and repeat-contact patterns. •     Interpretation of speech and text analytics output to surface recurring issues, intents and emerging risks. Key Responsibilities:

1. Executive and operational reporting •     Own the weekly and monthly Customer Operations performance pack. •     Design & maintain dashboards & scorecards giving visibility of performance across Contact Centre, IVR, chatbot, WhatsApp, email, social and digital self-service channels. •     Produce year-on-year, month-on-month and trend analysis, with commentary that explains movement and insights.
2. Root-cause and contact-driver analysis •     Analyse complaints, service disruptions, transaction failures and escalation trends to identify root causes and quantify their contact and cost impact. •     Quantify repeat contact and first-contact-resolution performance by intent and workcode, and identify the drivers behind each. •     Convert findings into recommendations with a named owner and an estimated benefit; track whether recommended actions were taken and what changed as a result.
3. Demand forecasting and capacity analytics •     Forecast contact volumes by channel and intent to support rostering, capacity planning and vendor resourcing. •     Model demand shocks and provide early warning of capacity pressure ahead of it materialising. •     Provide scenario and sensitivity analysis to support planning decisions on staffing, channel mix and deflection investment.
4. Vendor, channel and quality performance analytics •     Analyse performance across internal and outsourced servicing operations: service level, AHT, ASA, abandonment, occupancy, adherence, productivity and QA outcomes. •     Evaluate vendor performance against contractual SLAs, evidence gaps, and support commercial and performance discussions with analysis. •     Track CSAT, NPS, CES and complaint-resolution performance and identify what moves them.
5. Deflection and containment measurement •     Establish and maintain the deflection and containment baseline by intent across IVR, chatbot, WhatsApp and self-service •     Measure containment quality, not only containment volume: escalation rates, abandonment after containment, repeat contact following a contained interaction, and CSAT on AI-handled contacts versus agent-handled. •     Provide independent measurement in support of vendor evaluation, pilot assessment and benefits realisation for AI deployments.
6. Journey and AI performance analytics •     Identify and size the servicing journeys with the greatest deflection and automation potential, to inform use-case prioritisation. •     Analyse intent and conversation data — including speech and text analytics output — to support journey redesign, knowledge-base prioritisation and conversation design owned by Experience Transformation & Innovation. •     Monitor deployed AI servicing performance over time and flag degradation, drift in intent mix, or gaps in knowledge coverage.

JazzCash is an equal opportunity employer. We celebrate, support, and thrive on diversity and  are committed to creating an inclusive environment for all employees.