Senior Data Scientist (Credit) at Moniepoint Incorporated – Remote: Full Job Guide, Requirements & How to Apply

If you’ve been watching Nigeria’s fintech space with one eye on your career, you already know that Moniepoint isn’t just another payment company. It’s one of the fastest-growing financial technology platforms in Africa, and right now, it’s hiring a Senior Data Scientist (Credit) for a fully remote position. This is one of those rare roles that puts you at the centre of decisions affecting millions of people across the continent.

Whether you’re a seasoned data scientist ready to take on more responsibility or someone exploring what this role truly demands, this guide breaks everything down — from what you’ll actually do every day, to how the interview process works, and exactly how to apply.

Let’s get into it.

What Is This Role Really About?

Where Credit Science Meets Fintech Impact

The title says “data scientist,” but this isn’t a research lab position where you spend your days building theoretical models that gather dust. At Moniepoint, this role sits right at the intersection of data science, credit risk, and product delivery. You’re not just building models — you’re building models that decide who gets a loan, how much credit someone qualifies for, and at what price.

Think about that for a second. Nigeria has hundreds of millions of people who’ve historically been locked out of formal credit. Moniepoint wants to change that, and you’d be one of the people making it happen with data.

Why This Role Matters at Moniepoint

Moniepoint is aggressively expanding its consumer lending product. They’re onboarding over a million new customers every single month. That level of growth creates enormous pressure to get credit decisions right — not just fast, but fair, accurate, and scalable.

The Senior Data Scientist (Credit) is being brought in to build out the first real suite of credit risk models for the consumer side of the business. That means you’re not inheriting someone else’s messy codebase. You’re building from the ground up, which is both exciting and deeply consequential.

About Moniepoint Incorporated

From Nigerian Startup to Global Fintech

Moniepoint Incorporated started as TeamApt Limited in 2019 and has since grown into one of Africa’s most talked-about fintech companies. It recently became QED Investors’ first investment on the African continent — a huge vote of confidence from one of the world’s most respected fintech venture capital firms.

Today, Moniepoint processes over $17 billion in transactions every month. It powers the majority of Point of Sale (POS) transactions across Nigeria and has expanded into the UK. The company is fully remote-first, with a global team spread across multiple continents.

Moniepoint’s Mission and Reach in Africa

Moniepoint’s mission is simple but powerful: to enable financial happiness for every African, everywhere. That means building payment infrastructure, business banking tools, credit products, and financial management solutions that everyday people and businesses can actually rely on.

It’s a company with real users, real scale, and real problems to solve. And it’s still early days.

Job Details at a Glance

Detail	Info
Job Title	Senior Data Scientist (Credit)
Company	Moniepoint Incorporated
Location	Fully Remote
Experience Required	5+ years
Employment Type	Full-time
Application Portal	job-boards.eu.greenhouse.io/moniepoint
Closing Date	Not specified

Key Responsibilities of the Senior Data Scientist (Credit)

Building Credit Scoring and Behavioural Models

This is the core of the job. You’ll design, develop, and deploy credit scoring models that determine who qualifies for a loan, affordability models that estimate how much someone can comfortably repay, and behavioural models that track how customers interact with credit products over time.

These models don’t just sit in a notebook. They get embedded directly into real-time product systems, so your code is making live decisions at scale.

Running Experiments That Move the Business

A big part of this role is running structured experiments — A/B tests and similar frameworks — to understand what actually improves business outcomes. You might test different approval thresholds, explore the impact of a new feature in your model, or measure whether a change in credit limits affects repayment rates. You’re expected to design these experiments thoughtfully, analyze the results rigorously, and communicate your findings to both technical and non-technical stakeholders.

Working with Product Teams in Real Time

You won’t be working in isolation. Moniepoint expects its data scientists to partner closely with product squads to embed decision logic directly into live systems. That means you’ll need to understand product context, communicate with engineers, and sometimes make judgment calls about how a model should behave in edge cases.

You’ll also be responsible for mentoring colleagues on experimentation best practices and helping build a data-driven culture within the Consumer Credit team.

Other responsibilities include:

• Providing models to optimise collections, churn management, and user retention
• Ensuring data quality, compliance, and ethical model use
• Contributing to pricing strategy and credit limit modelling

Requirements and Qualifications

Educational Background

Moniepoint wants someone who’s comfortable with the mathematical foundations of data science. A degree or relevant qualification in a quantitative field is expected — Statistics, Mathematics, Engineering, Computer Science, or anything similar that gave you a solid grounding in numbers and analytical thinking.

Technical Skills You Must Have

Here’s what the role explicitly requires:

• 5+ years of experience in data science, decision science, or risk analytics within financial services
• Strong working knowledge of credit risk, consumer lending, and regulatory considerations
• Proficiency in SQL and at least one of Python or R
• Experience with A/B testing, machine learning, collections modelling, and churn management
• Ability to translate complex analyses into clear recommendations for business stakeholders

It’s worth noting that experience with machine learning is needed, but so is knowledge of more traditional statistical methods. Moniepoint wants someone who can decide when to use ML versus a simpler model — not just someone who reaches for a neural network every time.

Soft Skills and Work Style

Beyond the technical requirements, Moniepoint is looking for someone with:

• A high ownership mindset — you take problems seriously and follow through
• Comfort working in fast-paced, cross-functional teams
• Strong communication skills to explain technical findings to non-data audiences
• The ability to bring fresh thinking and challenge existing assumptions

What Moniepoint Offers You

Salary and Compensation

Moniepoint doesn’t publicly advertise salary figures for this role, but here’s what the company has confirmed it offers:

• Attractive salary (competitive within the African fintech market)
• Pension contributions
• Health insurance
• Monthly performance bonuses
• Additional benefits (details shared during the offer stage)

Based on industry benchmarks, senior data scientists in fintech roles at this level in Nigeria typically earn between ₦800,000 and ₦1,500,000 per month, with global remote roles often paid in USD or GBP depending on your location.

Culture, Learning, and Remote Flexibility

One of Moniepoint’s strongest selling points is its people-first culture. The company has deliberately built an environment where:

• All voices carry weight, regardless of seniority
• Knowledge sharing and internal technical talks are regular
• Learning and development is actively encouraged
• The team is genuinely diverse — global remote means you’ll work with colleagues across continents

This isn’t a company that treats remote work as a reluctant compromise. It’s built remote-first from the ground up.

The Moniepoint Hiring Process Step by Step

This is where most job guides fall short. They tell you the role exists but don’t help you understand what actually happens after you click “apply.” Here’s the full breakdown.

Stage 1 – Preliminary Phone Call

A recruiter will reach out to have an initial conversation. This is typically a 20–30 minute call to confirm your background, assess cultural fit, and explain the process. Be ready to talk about why you’re interested in credit data science specifically and what drew you to Moniepoint.

Stage 2 – HackerRank Coding Exercise (How to Prepare)

This is a structured online assessment that covers:

• Core data science theory — maths, statistics, and linear algebra
• Python fundamentals — data structures and algorithms

Don’t underestimate this stage. It’s not just a formality. To prepare well:

• Revise probability distributions, Bayes’ theorem, and hypothesis testing
• Practice SQL queries involving window functions and aggregations
• Brush up on Python data structures — lists, dictionaries, sets, and time complexity

Stage 3 – Take-Home Assignment Tips

After the HackerRank test, you’ll receive a take-home assignment. This is usually a practical data problem related to credit or lending. A few tips:

• Structure your code cleanly — they’ll review it carefully
• Document your assumptions and reasoning
• Don’t just show what the answer is; show how you think
• Focus on insight, not just accuracy

Stage 4 – Technical Interview

A Lead in Moniepoint’s Data Science team will walk through your take-home assignment with you in depth. They want to understand your decision-making process. Why did you choose one model over another? What would you do differently with more time or data? Be honest and thoughtful here.

Stage 5 – Behavioural and Hiring Manager Interview

The final interview covers both technical depth and how you work with others. Expect questions like:

• Tell me about a time you had to explain a model’s limitations to a non-technical stakeholder
• How do you balance model accuracy with fairness or regulatory constraints?
• Describe a situation where your analysis changed a business decision

How to Write a Winning Application

Tailoring Your CV for a Credit Data Science Role

Your CV should make it immediately obvious that you understand credit risk. Don’t just list your tools — explain the business impact of the models you’ve built. Use phrases like “reduced default rates by X%”, “improved approval accuracy on underserved segments”, or “reduced credit loss ratio through feature engineering.”

Highlight any work you’ve done in:

• Consumer lending or microfinance
• Regulatory compliance (CBN guidelines, GDPR, responsible AI)
• A/B testing in production systems
• Python-based model deployment pipelines

What to Highlight in Your Cover Letter

Keep it short and direct. In three to four paragraphs, tell them:

1. Why you’re excited specifically about credit data science at scale in Africa
2. One concrete example of a model or experiment you built that had measurable impact
3. Why Moniepoint’s stage of growth is the right environment for you

Skip the generic opener. “I am writing to apply for…” is not a hook. Start with something that shows you understand what Moniepoint is trying to do.

Is This Role Right for You?

Signs You’re a Strong Fit

You’re probably a strong candidate if:

• You’ve built credit scoring or risk models in a fintech, bank, or lending company
• You’re comfortable owning a model end-to-end — from data sourcing to production deployment
• You genuinely enjoy explaining data insights to people who don’t speak Python
• You thrive in ambiguity and don’t need someone to hand you a perfectly clean dataset
• You care about the social impact of fair credit access in emerging markets

How It Compares to Similar Roles in Nigerian Fintech

Roles like this at companies like Flutterwave, PalmPay, or Carbon tend to have similar technical requirements but differ in scope. At Moniepoint, the specific focus on consumer credit at scale — and the fact that you’d be building the first proper suite of models — gives you unusually high ownership and visibility for a senior role. If you want to build something meaningful rather than maintain something already built, this opportunity stands out.

How to Apply for the Senior Data Scientist (Credit) Role at Moniepoint

Applying is straightforward:

1. Visit the official Moniepoint careers portal at moniepoint.com/careers
2. Search for “Senior Data Scientist (Credit)”
3. Click the role and select “Apply”
4. You’ll be redirected to the Greenhouse application system
5. Upload your CV, complete the application form, and submit

You can also apply directly via: job-boards.eu.greenhouse.io/moniepoint/jobs/4808999101

There’s no official application closing date listed, which means the role could close at any time once they find the right person. Don’t wait.

Frequently Asked Questions

Is Moniepoint a good company to work for? Yes, by most accounts. Moniepoint has built a strong reputation for its people-first culture, competitive compensation, and genuine remote-first flexibility. The company has grown rapidly, which means there are real opportunities for career growth — but also the reality of a fast-paced environment that isn’t for everyone.

What is the salary of a Senior Data Scientist at Moniepoint? Moniepoint doesn’t publish exact salary figures publicly, but senior data science roles in Nigerian fintech typically range from ₦800,000 to ₦1,500,000 monthly, with global remote positions sometimes compensated in USD or GBP. The role also includes health insurance, pension, and monthly bonuses.

How hard is the Moniepoint interview process? It’s thorough. There are five stages, including a HackerRank assessment and a take-home assignment reviewed in a live technical interview. It’s not designed to trick you, but it does reward candidates who can clearly communicate their thinking and show practical impact from past work.

Do I need a master’s degree to apply? Not necessarily. The requirement is a degree or qualification in a quantitative field. What matters more is five or more years of relevant experience in data science or risk analytics within financial services.

Can I apply from outside Nigeria? Yes. The role is fully remote, and Moniepoint has a globally distributed workforce. The company doesn’t restrict applications to Nigerian residents, though you should be able to work within reasonable overlap hours with the team.

What programming languages does Moniepoint use for data science? The role requires proficiency in SQL and at least one of Python or R. Python is by far the more common choice in the industry and likely the preferred language at Moniepoint given its machine learning tooling.

What does “credit data science” mean in practice? It means using statistical and machine learning techniques to make lending decisions. That includes building models that predict the likelihood of a borrower repaying a loan, deciding how much credit to offer, pricing that credit appropriately, and identifying when a borrower is at risk of defaulting so the business can intervene early.

 

What happens if there’s no closing date listed? Apply as soon as you can. When a job listing says “closing date not specified,” it often means the company will close applications the moment they find the right candidate. Delaying your application reduces your chances significantly.