Machine Learning Engineer (Remote) at Moniepoint Incorporated

Moniepoint Incorporated is a global business payments and banking platform and recently became QED Investors’ first investment in Africa. We are the partner of choice for over 600,000 businesses of all sizes, powering the dreams of SMBs and providing them with equal access to the tools they need to grow and scale.

We are recruiting to fill the position below:

Job Title: Machine Learning Engineer

Location: Remote
Job type: Full time

What You’ll Do

• Lead high-impact projects: Design and deliver end-to-end data science solutions that support product innovation and business strategy.
• Uncover insights: Analyze large, complex datasets to identify trends, surface opportunities, and influence key decisions.
• Build models: Develop and deploy predictive and prescriptive models using machine learning and statistical techniques.
• Enable experimentation: Design A/B tests and causal inference studies to help teams learn quickly and make informed choices.
• Collaborate cross-functionally: Work closely with product managers, engineers, and business leaders to understand goals and deliver data-driven solutions.
• Promote data fluency: Build dashboards, tools, and frameworks to enable self-service analytics and scale your impact across teams.

To succeed in this role, you should have

• 5+ years of experience as a Data Scientist, ideally in fast-paced or high-growth environments
• Proficiency in SQL and experience working with large-scale data systems (e.g., Redshift, BigQuery, Snowflake).
• Strong analytical and statistical skills; fluency in Python or R.
• Experience with machine learning libraries (e.g., scikit-learn, XGBoost) and data visualization tools (e.g., Tableau, Looker, Plotly).
• Solid understanding of experimental design, hypothesis testing, and causal inference.
• Ability to distill complex data problems into clear, actionable insights.
• BSc/MSc/PhD in a quantitative field such as Statistics, Computer Science, Mathematics, Economics, or similar.

Experience with the following would be a plus

• Experience with deep learning, NLP, or time-series forecasting.
• Knowledge of tools for building production data pipelines (e.g., Airflow, dbt).
• Familiarity with business domains like fintech, e-commerce, healthcare, etc..

What we can offer you

• Culture - We put our people first and prioritize the well-being of every team member. We have 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, annual bonus, plus other benefits.
• The opportunity to drive impact through data in a high-growth environment.
• A collaborative culture with room to grow and experiment.
• Access to rich data and a modern analytics stack.

Application Closing Date
Not Specified. 

Method of Application
Interested and qualified candidates should:
Click here to apply online

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 Engineering Team to review your take-home assignment in depth
• A behavioural and technical interview with a member of our Executive team