Job description
Title: Expert Product Analytics Grade Level: L1/L2 Location: Islamabad Last Date to Apply: 21st July 2026 What is Expert Product Analytics?
As an Expert Product Analytics, you will work closely with the product management team to drive data-led decision-making for wealth management products.
You will play a pivotal role in collecting, analyzing, and interpreting complex data to support the development and optimization of lending, savings, insurance, and investment products.
You will collaborate with multiple stakeholders to turn data into actionable insights, enabling the team to make strategic decisions.
What does Expert Product Analytics do?
1. AI-Driven Product Insights & Development Support the product management team in developing and refining wealth and lending products using data-driven insights.
Build and deploy AI and machine learning models for credit scoring, customer segmentation, churn prediction, and product recommendation.
Contribute to end-to-end model lifecycle: feature engineering, training, validation, and monitoring.
2. Data Analysis & Modeling Conduct advanced analysis using Python, R, SQL, Spark, and Hadoop to extract insights from large-scale structured and unstructured data.
Develop predictive and risk models to forecast loan performance, default probabilities, and portfolio health.
Apply statistical and machine learning techniques (e.
g., regression, decision trees, ensemble models, neural networks).
3. Product Performance Monitoring Build and maintain real-time dashboards and KPI trackers to evaluate product performance across lending, savings, and insurance verticals.
Identify trends, anomalies, and growth opportunities using automated reporting tools (e.
g., Power BI, Tableau).
4. Market & Customer Analytics Analyze customer behavior, transaction patterns, and market dynamics to improve targeting, credit eligibility, and retention strategies.
Generate actionable insights to support pricing, product feature design, and campaign optimization.
5. Experimentation & Continuous Improvement Design and evaluate A/B tests, experiments, and pilots to validate new product hypotheses.
Collaborate with engineering and product teams to integrate feedback loops into product models for continuous learning.
6. Risk Analytics & Governance Partner with the Risk and Compliance teams to enhance credit risk assessment frameworks using AI-driven models.
Monitor model drift and performance degradation, ensuring accuracy and explainability JazzCash is an equal opportunity employer.
We celebrate, support, and thrive on diversity and are committed to creating an inclusive environment for all employees.
Why Join JazzCash?
As one of the largest digital financial services providers in Pakistan, our objective is to continue to change the lives of our customers for the better.
Recognized as one of the leading employers in the country, JazzCash epitomizes the philosophy that each JazzCash employee is passionately living a better life every day, inspired and enabled by visionary leadership, a unique professional culture, a flourishing lifestyle, and continuous learning and development.
Our core values include qualities essential for a positive organizational culture - truthfully guiding entrepreneurial and innovative mindsets, harnessing professional and interpersonal collaboration, and fostering across-the-board customer obsession.
This is an opportunity for someone who wants to be part of something transformative, someone who can play a critical role in driving our success.
Together, we can empower millions more with the tools necessary to progress in an increasingly digital economy.
What are we looking for and what does it require to be Expert Product Analytics?
Bachelor’s or master’s degree in data science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
2–4 years of experience in data science, machine learning, or advanced analytics — preferably in fintech, banking, or digital financial services.
Strong command of Python, R, SQL, and familiarity with big data frameworks (Spark, Hadoop).
Experience building and deploying AI/ML models in production environments.
Understanding of credit scoring, risk analytics, and financial modelling is highly preferred.
Proficiency in data visualization tools (Power BI, Tableau) and cloud environments (AWS, GCP, Azure).
This job post has been translated by AI and may contain minor differences or errors.
