Machine Learning Engineer

Moniepoint Inc. is Africa’s all-in-one financial ecosystem, helping 10 million businesses and individuals access seamless payments, banking, credit, and business management tools since 2019.

As Nigeria’s largest merchant acquirer, it powers most of the country’s Point of Sale (POS) transactions. Through its subsidiaries, Moniepoint Inc. processes $22 billion monthly for its customers while operating profitably.

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’re looking for an experienced Senior Data Scientist who’s excited to solve meaningful problems, collaborate across teams, and turn complex data into clear, actionable insights. You’ll work at the intersection of data, product, and engineering to uncover insights, guide strategic decisions, and develop models that enhance user experience and business outcomes.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

• →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.

• 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 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.

• 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.

• 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

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.