Moniepoint Wants a Growth Data Analyst — Remote, Lagos

This is not a reporting role. Moniepoint wants someone who shapes product decisions from opportunity sizing to post-launch impact analysis.

The position sits inside the payments product team, focused on user acquisition, retention, and growth analytics. You will own the full analytics lifecycle for marketing and growth, not just build dashboards but drive the thinking behind them. It is full-time and remote, listed under Lagos.

About Moniepoint Inc

Moniepoint is one of Nigeria's most consequential fintech companies, not by hype but by reach. The company processes payments for businesses across Nigeria at a scale that puts it among the country's highest-volume transaction processors. In 2024, it was named Africa's fastest-growing fintech by the Financial Times. It operates across payments, banking, credit, and business management tools, with a stated mission to digitize Africa's real economy. Working here means your analysis touches real financial infrastructure used by hundreds of thousands of businesses daily.

What the Role Involves

The title says Data Analyst. The scope reads closer to a product analytics lead for the growth function. Day to day, you will:

• Partner with product managers, engineers, and data teams to surface insights that guide sales, marketing, and growth decisions
• Translate business and product questions into analysis, then turn that analysis into actions the team can actually execute
• Build and maintain self-service dashboards and visualisation tools that stakeholders use independently
• Own end-to-end analytics for the marketing and growth product from data requirements and opportunity sizing through experimentation and post-launch measurement
• Design and analyse A/B tests, multivariate experiments, clustering models, and supervised learning applications to solve high-impact business problems
• Act as the strategic link between technology, business, and product teams

This is a high-ownership role. "Own end-to-end" at Moniepoint's scale means your output has direct commercial consequences.

What They Want

Must Have:

• 3 to 4 years of professional experience in a quantitative analysis role outside academic or internship settings
• That experience must come from a tier-one consulting firm, investment bank, or tech company with a serious programming culture. The listing is explicit about this
• Strong SQL skills — tested during the interview process, not just self-reported
• Demonstrated experience designing and analysing experiments in digital products, such as A/B testing, and multivariate testing
• Experience with statistical programming in Python, Pandas, SciPy, and Jupyter notebooks
• Knowledge of visualisation tools, Tableau, Looker, or comparable platforms
• Experience applying statistical modelling and advanced analytics to shape product decisions
• Excellent written and spoken English

Nice to Have:

• Specific experience in payments, fintech, or consumer product analytics
• Familiarity with data engineering workflows

Job Salary and Benefits

Moniepoint has not disclosed a salary range for this role.

For honest market context: Data analysts with 3 to 4 years of experience at Nigerian fintechs of Moniepoint's scale typically earn between ₦500,000 and ₦1,200,000 per month, depending on seniority, negotiation, and whether the role is naira or dollar-denominated. Moniepoint has been known to offer competitive packages relative to the Nigerian market, given its funding and scale—but confirm figures directly during the interview process.

Is This Open to Nigerians?

Yes. The role is listed as Lagos-based and remote.

Payment will almost certainly be in naira given the Lagos location framing, but dollar denomination is worth clarifying during the process given Moniepoint's international footprint.

How to Apply — Step by Step

1. Go directly to Moniepoint's Greenhouse page and find the data analyst listing or apply using our listing.
2. Prepare your CV. Lead with quantitative impact, not just tools used, but also what changed because of your analysis. Moniepoint will look for evidence of product-shaping work, not just reporting.
3. Prepare for a SQL test. The listing explicitly states SQL is tested during the process. Brush up on window functions, CTEs, and complex joins — these are standard at this level in fintech interviews.
4. Prepare your experiment portfolio. If you have designed or analyzed A/B tests, document the methodology, sample sizes, and outcomes. This is a core requirement and likely to come up in the technical interview.
5. Submit your application through Greenhouse. No cover letter requirement is stated.
6. Apply now. No deadline is listed. Moniepoint is an active hirer, and strong roles at this level fill quickly once the right candidate appears.

Common mistakes to avoid:

• A CV that lists Python and SQL without showing what problems they solved
• Underselling experiment design experience? If you have run A/B tests, name the product, the hypothesis, the result, and the business impact
• Applying without reviewing your SQL fundamentals, the test is confirmed, and there is no reason to walk in underprepared

Verdict

Moniepoint is a genuinely strong place to build a data career in Nigerian fintech right now. The company has the scale, the data volume, and the product complexity to give a good analyst real problems worth solving. This is not a role where you spend your days formatting PowerPoint slides — the scope makes that clear.

This is ideal for quantitative analysts from consulting, investment banking, or product-heavy tech companies who want to move into fintech and work on growth problems at scale. If you have experiment design experience and strong SQL, this role fits your profile closely.

Who should skip it: If your analytics background is primarily in reporting, Excel-based analysis, or business intelligence without statistical modeling exposure, the technical bar here is likely above where you are right now. The SQL test alone will surface that gap quickly.

One tip to stand out: Moniepoint specified tier-one firms and heavy programming environments as the experience benchmark. If your background fits that description, say so explicitly in your CV summary; do not make the recruiter infer it. Name the company, the scale of data you worked with, and the product decisions your analysis influenced. Specificity at this level reads as seniority.

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