Senior Data Scientist (Credit)
Moniepoint is hiring a Senior Data Scientist (Credit) for a remote role open to applicants in Portugal. Level rates it ; you can apply on Level.
AI in this role
Senior Data Scientist to build and deploy credit risk scoring, affordability, and behavioral machine learning models at scale.
Who we are
Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments, banking, credit, cross-border, and business management tools each month.
As Nigeria’s largest merchant acquirer, we power most of the country’s point-of-sale (POS) transactions. Through our subsidiaries, Moniepoint Inc. processes over $250 billion in digital payment transaction value annually.
About the role:
At Moniepoint, data is at the core of everything we do. We are a customer-centric company, and your work will enable our teams to make informed, data-driven decisions that directly impact the success of our business. We are seeking a data-driven, impact-oriented Senior Data Scientist to power Moniepoint’s consumer lending decisions at scale. You will build the models, experiments, and insights that shape how we acquire, underwrite, and retain millions of customers across Nigeria and Africa.
This role is pivotal in driving our pricing, credit limit modelling, and credit model deployment strategy in a growing business with unparalleled opportunities to give access to millions of customers. You’ll collaborate with our amazing Consumer Credit team and drive how we think about risk ranking, product offering, and data infrastructure to create the best personalised offers for our customers. You’ll be responsible for building our first suite of credit risk models and help drive a culture of how we should think about machine learning vs more traditional methods - bringing fresh thinking to inspire both the team and our customers.
Sitting at the intersection of data science, credit risk, and product, you’ll translate complex data into actionable decisions that drive growth with healthy portfolio performance.
Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.
What You’ll Do
- Develop and deploy credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
- Design and run experiments to optimise approval rates, loss rates, and profitability
- Partner with product squads to embed decision logic into real-time systems
- Ensure data quality, compliance, and ethical use of models across all decisioning processes
- Mentor product squads on best practices in experimentation and data-driven decision-making
- Provide models to optimise outcomes in collections, churn management and user retention
We would love to hear from you if…
- You’re comfortable with Statistics and have a Degree or qualifications in a quantitative field (Statistics, Mathematics, Engineering or similar)
- You have +5 years of experience in data science, decision science, or risk analytics within financial services
- Working knowledge of credit risk, consumer lending, and regulatory considerations
- Proficiency in SQL and at least one modelling/programming language (Python, R)
- Experience with A/B testing, machine learning, collections modelling and churn management
- Ability to translate complex analyses into clear recommendations for business stakeholders
- High ownership mindset and comfort working in fast-paced, cross-functional teams
What we can offer you
- Culture: We put our people first and prioritise the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
- Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
- Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits
What to expect in the hiring process
- A preliminary phone call with the recruiter
- A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
- A take-home assignment
- A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
- A behavioural and technical interview with the hiring manager
Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.
How we rate this
Senior Data Scientist (Credit) at Moniepoint rates 80 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
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Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $170k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
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- What's a project where you used Python hands-on?
- Walk me through how you've used Machine learning in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Python and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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