Data Analyst - Credit & Product
MoPhones
Our Pitch – Who We Are
MoPhones is on a mission to empower Africans with high-quality, premium smartphones that do not break the bank. By combining a trusted online marketplace, local retail presence, and integrated financing, MoPhones makes renewed devices accessible, affordable, and better for the planet through circular, lower-waste models.
At MoPhones, everything we do is guided by three values: Authenticity, Ownership, and Focus.
- Authenticity: We build trust through honesty, transparency, and real care. From clear pricing and fair policies to dependable, renewed devices, we stand behind what we promise and treat every customer with dignity.
- Ownership: We take responsibility for outcomes. When customers choose MoPhones, they should never feel alone, we solve problems end-to-end, stand behind our products, and take pride in delivering excellent work.
- Focus: We prioritise what matters most: making high-quality smartphones accessible and affordable. We stay disciplined about simplicity, impact, and solutions that expand access to technology across our communities.
The team works with leading refurbishers and a growing network of sales agents and outlets to bring warrantied devices and flexible instalment plans to customers across Kenya, with ambitions to scale across Africa. The culture is mission-driven, data-informed, and deeply performance-oriented, with a strong bias toward ownership, coaching, and experimentation.
Why This Role Exists
MoPhones sits at the intersection of e-commerce, device financing, and consumer credit. The data exists: payment histories, bureau records, device telemetry, funnel metrics, promotional outcomes; but the analytical infrastructure to make sense of it does not yet. Decisions across the product and credit functions are being made without the depth of insight the business needs to optimise conversion, underwriting, portfolio quality, and customer lifetime value.
This is the first embedded analyst role spanning both product and credit. You will build the self-service BI infrastructure that puts data directly into stakeholders’ hands and own the deep analytical investigations that explain what is actually driving outcomes; from acquisition through to repayment.
About the Role
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.
What We Are Looking For
Required
3–5 years of experience in an analytics or BI role, with a track record of building self-service dashboards and automated reporting that reduce ad-hoc analyst dependency.
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 in messy business data.
Demonstrated ability to communicate analytical findings to non-technical stakeholders in writing and in person.
Nice to have
Credit or fintech domain knowledge: delinquency metrics, collections workflows, credit bureau data (TransUnion, Metropol, CRB), or underwriting concepts.
E-commerce or product analytics experience: funnel analysis, conversion optimisation, cohort analysis, or customer segmentation.
Python or R for statistical modelling, data visualisation, or predictive analytics beyond SQL.
Modern data stack experience: dbt, Snowflake, Holistics, Airbyte/Keboola, or similar.
How you work
Enablement mindset – you build tools and infrastructure that make others autonomous, not just answer questions repeatedly.
Statistical rigour – you apply proper analytical frameworks to messy business problems and know when the data supports a conclusion and when it does not.
Ownership and initiative – comfortable building from ambiguity in a fast-paced environment with high autonomy.
Cross-functional range – you move confidently between product and credit contexts and adapt your analysis and communication to each audience.
What You Will Get From Us
- Compensation - Competitive salary benchmarked to the Nairobi data and fintech market, aligned with your experience and impact.
- Location - On-site, Nairobi: embedded daily with the credit and risk team.
- Medical & Accident Coverage - Group personal accident and medical coverage for your well-being and security.
- Leave & Public Holidays - Paid time off and public holiday benefits.
- Learning & Development - A foundational role — you are the first embedded analyst in the credit team, building infrastructure and insight frameworks from the ground up.
Come Make an Impact With Us: Join MoPhones and help build a more inclusive future of mobile access in Africa.
MoPhones is committed to building a diverse, equitable, and inclusive team where every person can contribute, grow, and belong, regardless of their background, identity, or lived experience. The company actively welcomes candidates from underrepresented and historically excluded groups across gender, ethnicity, disability, age, religion, sexual orientation, and socio-economic background, and hires based on skills, potential, and shared commitment to the mission.
If you are excited about this opportunity but do not meet every single requirement, you are strongly encouraged to apply. MoPhones knows that great teams are built by people with different paths and perspectives.
Accommodations can be provided throughout the recruitment process on request, because an inclusive candidate experience is essential to how MoPhones operates.