Data Analyst

M-KOPA

Nairobifull time~KES 130k – 190k/mo3w ago

Quick Take

The Role

Build dashboards, write complex SQL queries, and translate data insights into actionable recommendations for commercial and operations teams at a fast-growing fintech serving millions of Africans.

You Need

Strong SQL skills, 2+ years of data analyst experience, and proficiency with Python (pandas/numpy) and at least one BI tool like Power BI, Tableau, or Looker.

You Get

Above-market salary of up to KES 190,000, a high-impact role at one of Africa's most recognised fintech companies, and exposure to large-scale consumer and credit data across multiple African markets.

Job Description

•Role Overview

M-KOPA is a connected asset financing platform that has already transformed the lives of more than 5 million customers across the African continent. By providing access to essential assets through affordable, flexible financing, M-KOPA is on a mission to expand financial inclusion at scale — and data sits right at the heart of that mission.

To support this growth, M-KOPA is looking for a talented Data Analyst to join the team in Nairobi. In this role, you will be responsible for converting complex, large-scale datasets into clear, actionable insights that drive better decisions across commercial and operational functions. If you are passionate about using data to create real-world impact for everyday people, this is an opportunity worth exploring.

•Key Responsibilities

Design, develop, and maintain dashboards and reports that serve the needs of commercial and operations teams
Write and optimise sophisticated SQL queries to extract, transform, and analyse large volumes of data
Investigate business questions independently and communicate findings clearly to senior stakeholders
Work closely with data engineers to enhance data quality standards and ensure pipeline reliability
Assist in the analysis of A/B tests to inform product development and credit-related decisions

•Required Skills & Experience

A minimum of 2 years of hands-on experience in a data analyst position
Advanced SQL proficiency — you should be comfortable writing complex queries without hesitation
Practical experience using Python for data manipulation, particularly with libraries such as pandas and numpy
Working knowledge of at least one BI or visualisation tool, including Power BI, Tableau, Looker, or Metabase
Strong communication skills with the ability to translate technical findings into language that non-technical audiences can easily understand
Experience with dbt for data transformation is an added advantage
A background in financial services or credit analytics would also be beneficial

•Who Should Apply

This role is best suited for an analytically minded professional who is comfortable working with large, complex datasets and is equally confident presenting insights to senior decision-makers. You enjoy asking the right questions, digging into the numbers, and turning what you find into clear recommendations. You are collaborative by nature, able to work alongside data engineers and cross-functional teams, and you take pride in producing high-quality, reliable analysis. Familiarity with the financial services landscape — particularly credit products in emerging markets — will help you hit the ground running, though it is not a strict requirement.

•How to Apply

Interested candidates should apply directly through M-KOPA's official recruitment channels. Submit your application for the Data Analyst position based in Nairobi, ensuring your CV clearly highlights your SQL experience, Python skills, and any relevant BI tools you have worked with. Only shortlisted candidates will be contacted.

Requirements Breakdown

Must Have

2+ years of experience in a data analyst role
Strong SQL skills for writing complex queries on large datasets
Experience with Python (pandas, numpy) for data manipulation
Familiarity with at least one BI tool (Power BI, Tableau, Looker, or Metabase)
Excellent communication skills to present findings to non-technical stakeholders

Nice to Have

Experience with dbt (data build tool) for data transformation
Knowledge of financial services or credit analytics
Experience supporting A/B test design and analysis
Familiarity with data pipeline or data quality concepts

Don't meet every requirement? Tailor your CV to close the gap →

Salary Context

Above market rate for a mid-level Data Analyst in Nairobi

Data Analyst salaries in Nairobi typically range from KES 80,000 to KES 150,000 per month for mid-level roles, making M-KOPA's upper band of KES 190,000 notably competitive. Pay in this field is influenced by sector (fintech commands a premium), SQL and Python depth, and experience with large or complex datasets.

About M-KOPA

M-KOPA is a connected asset financing platform that has transformed access to essential goods for over 5 million customers across Africa, allowing low-income households to acquire smartphones, solar energy systems, and other assets through affordable micro-payments. Headquartered in Nairobi, M-KOPA operates at the intersection of fintech, data, and social impact, using technology and credit analytics to serve customers who are largely underserved by traditional financial institutions. Working at M-KOPA means your analysis directly influences credit decisions, product development, and the daily lives of everyday Africans — making it a compelling destination for data professionals who want their work to matter.

Likely Interview Questions

1
Walk us through a complex SQL query you have written — what was the business problem, and how did you structure your approach?
2
How have you built or maintained a dashboard for a non-technical team? What decisions did you make about what to include, and how did stakeholders respond?
3
Describe a time you investigated an unexpected pattern in data. How did you diagnose the root cause and communicate your findings to leadership?
4
Have you supported an A/B test from design to analysis? How did you ensure statistical validity and present results to decision-makers?
5
How would you approach improving data quality in a pipeline where upstream data is inconsistent or incomplete?

Application Tips

Showcase specific SQL complexity in your CV — mention window functions, CTEs, or query optimisation on million-row datasets rather than just listing 'SQL' as a skill.
Highlight any experience in financial services, credit scoring, or working with transactional data, as M-KOPA sits at the heart of consumer lending and this context will set you apart.
Include a link to a portfolio, GitHub repository, or dashboard screenshot that demonstrates real work — M-KOPA is a data-driven company and showing rather than telling your analytical ability will make a strong impression.

Career Path

Roles that lead here

Junior Data Analyst

Business Intelligence Analyst

Data Engineer (junior)

Financial Analyst with SQL exposure

YOU

Where this leads

Senior Data Analyst

Analytics Manager

Data Science Manager

Head of Business Intelligence

Skills & Keywords

SQLPythonPower BIData Modellingdbt

Honest Assessment

Green Flags

Transparent and competitive salary range (KES 130,000–190,000) signals respect for candidates' time and sets clear expectations.
M-KOPA is a well-established, high-growth African fintech with real scale (5 million+ customers), offering genuine career development and brand credibility on a CV.
The role spans commercial, operations, product, and credit teams — providing unusually broad exposure for a single analyst position.
Collaboration with data engineers and involvement in pipeline reliability suggests a mature data function where an analyst can grow technical skills beyond just reporting.

Watch Out

The job description does not mention remote or hybrid work arrangements, which may be a concern for candidates outside Nairobi or those seeking flexibility.
No mention of benefits, leave entitlement, or learning and development budget — worth clarifying during the interview process.

A Day in the Life

☀️

A typical week might start with a Monday sync with the commercial team to review a sales performance dashboard you maintain in Looker, followed by an ad-hoc SQL deep-dive to explain a dip in customer repayment rates flagged by the credit team. Mid-week, you could be collaborating with a data engineer in a Slack thread to resolve a data quality issue in the payments pipeline, while also preparing a slide deck summarising A/B test results from a new product feature for a Friday presentation to senior leadership. By Thursday you are writing Python scripts in a Jupyter notebook to clean and reshape a raw dataset for a new operations report — with your work feeding directly into decisions that affect millions of customers across Kenya and beyond.

Frequently Asked Questions

What qualifications do I need to become a Data Analyst at M-KOPA?

You need at least 2 years of experience in a data analyst role, strong SQL skills, Python proficiency (pandas and numpy), and hands-on experience with a BI tool such as Power BI, Tableau, Looker, or Metabase. A formal degree is not explicitly required, though a background in a quantitative field is typically expected in roles like this.

Is the M-KOPA Data Analyst role remote or office-based?

The posting lists the location as Nairobi with no mention of remote or hybrid options, so candidates should assume this is an in-office or Nairobi-based role and confirm the working arrangement directly with M-KOPA during the application process.

How much does a Data Analyst at M-KOPA earn?

M-KOPA is offering KES 130,000 to KES 190,000 per month for this role, which is above the typical market rate for mid-level Data Analysts in Nairobi and reflects the company's fintech premium and the seniority expected of the successful candidate.

What are the career growth opportunities for a Data Analyst at M-KOPA?

Given M-KOPA's scale and data maturity, this role offers a strong path into senior analytics, data science, or analytics management positions — the cross-functional exposure across credit, product, and commercial teams also builds the breadth needed to move into leadership or specialist data science roles over time.

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