Data Analyst - Credit & Product

The Data Analyst – Product & Credit reports to the Senior Data Analyst and works daily across both the product and credit/risk teams. You will partner closely with the Analytics Engineering Lead on technical foundations while owning the analytical insight layer that informs strategy on both sides of the business.

The role has two primary modes of work:

• Enablement: Building self-service BI tools, dashboards, and automated reporting so that product, commercial, and credit stakeholders have immediate access to performance data without analyst bottlenecks.
• Deep analysis: Owning the causal and attribution investigations that correlate complex variables — funnel behaviour, promo cycles, device performance, payment patterns — to explain the true drivers of business outcomes.

This is a solo contributor role. You will not have direct reports, but you will be the analytical partner the product and credit teams rely on daily. You are expected to work with high autonomy, build from ambiguity, and communicate findings to non-technical stakeholders clearly.

Key Responsibilities

Product Analytics

• Design and maintain dashboards covering acquisition funnels, conversion rates, channel performance, and customer segmentation across online and retail.
• Analyse the impact of promotional campaigns, pricing changes, and device mix decisions on conversion, revenue, and customer lifetime value.
• Partner with commercial and marketing stakeholders to design experiments (A/B tests, holdout groups) and deliver attribution analysis that separates signal from noise.
• Identify behavioural patterns in the customer journey that inform product development, UX decisions, and go-to-market strategy.

Credit and Portfolio Analytics

• Build and maintain self-service dashboards for portfolio health, delinquency trends, collections performance, and risk segmentation.
• Conduct causal investigations correlating device performance, customer demographics, promotional history, and payment behaviour to identify true default drivers.
• Support underwriting optimisation through data-driven analysis of approval criteria, score thresholds, and policy change outcomes.
• Translate credit performance data into clear, actionable recommendations for the credit and risk leadership team.

BI Infrastructure and Data Quality

• Design and automate data pipelines that transform raw credit bureau data, payment histories, and operational systems into reliable, production-grade datasets.
• Partner with the Analytics Engineering Lead to establish data quality standards, documentation practices, and analytical frameworks that enable progressive data autonomy across teams.
• Reduce dependency on ad-hoc analyst requests by building repeatable, self-service data products.

Requirements

• 3–5 years of experience in an analytics or BI role, with a track record of building self-service dashboards and automated reporting.
• Advanced SQL and data transformation expertise: dimensional modelling, ETL/ELT pipelines, and production-grade dataset design.
• Solid grounding in statistical methods: A/B test design, regression analysis, and the ability to distinguish correlation from causation.
• Demonstrated ability to communicate analytical findings to non-technical stakeholders in writing and in person.
• Bachelor's degree or Higher National Diploma (BA/BSc/HND).

How to Apply

Interested and qualified candidates should visit the official application portal to submit their application: Apply for Data Analyst at MoPhones. This link redirects to the official hiring site at mophones.talentlyft.com.