Machine Learning Engineer (Remote) at Moniepoint Incorporated

Lagos
April 16, 2026
Remote
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Job Description

Moniepoint Incorporated is seeking a skilled Machine Learning Engineer to design and deploy data-driven solutions that power product innovation and business growth. This role is ideal for professionals who enjoy working with large datasets, building scalable models, and collaborating across teams to solve complex business problems.

Job Responsibilities

  • Lead end-to-end machine learning and data science projects from concept to deployment
  • Analyze large and complex datasets to uncover trends, insights, and business opportunities
  • Develop, test, and deploy predictive and prescriptive machine learning models
  • Design and implement A/B testing and experimentation frameworks
  • Collaborate with product managers, engineers, and stakeholders to deliver data-driven solutions
  • Build dashboards and analytics tools to support self-service data access across teams

Job Requirements

  • Minimum of 5 years’ experience in data science or machine learning roles
  • Strong proficiency in SQL and experience with large-scale data platforms such as Redshift, BigQuery, or Snowflake
  • Advanced knowledge of Python or R for data analysis and model development
  • Hands-on experience with machine learning libraries such as scikit-learn or XGBoost
  • Solid understanding of statistics, experimental design, and causal inference
  • Ability to translate complex data into clear, actionable insights
  • Bachelor’s, Master’s, or PhD in a quantitative field such as Computer Science, Statistics, Mathematics, or Economics

Additional Skills (Optional)

  • Experience with deep learning, natural language processing, or time-series forecasting
  • Familiarity with data pipeline tools such as Airflow or dbt
  • Exposure to industries such as fintech, e-commerce, or healthcare

Benefits

  • Competitive salary package with pension, health insurance, and annual bonus
  • Learning and development opportunities, including training and knowledge-sharing sessions
  • Collaborative work environment with opportunities for growth and innovation
  • Access to modern analytics tools and rich datasets

Hiring Process

  • Initial screening call with a recruiter
  • Coding assessment via HackerRank (covering data science fundamentals and Python)
  • Take-home assignment
  • Technical interview with an engineering lead
  • Final behavioral and technical interview with an executive team member

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