AI / ML Engineer at Contec Global Group in Lagos

Position Overview

As a Intermediate AI/ML Engineer, you will design, formulate, and deploy machine learning models to solve real-world challenges in fraud discovery, credit scoring, transaction supervising, and client personalization. You’ll collaborate with data engineers, backend developers, and cross-functional teams to convert business needs into AI-driven initiatives that scale.

Primary duties

• Carry out investigative data evaluation, function engineering, and statistical evaluation to uncover patterns and enhance model precision.
• Manage data cleaning, preprocessing, and coordinating imbalanced/sophisticated Financial technology data collections.
• Design and evaluate strategic trials (e.g., A/B running test) to confirm model business effect.
• Formulate, educate, and deploy ML models for fraud discovery, risk evaluation, credit scoring, and personalization.
• Work alongside Development-operations team to guarantee premium quality, dependable data pipelines for ML task volumes.
• Enhance models for effectiveness, scalability, and low latency in generation financial technology environments.
• Execute explainable AI (XAI) methods to guarantee model transparency and adherence with financial rules.
• Constantly track and enhance deployed models with instantaneous data response loops.
• Support to the design of APIs for model inference and consolidation into core financial technology applications.
• Stay informed with emerging AI/ML methods, especially in the financial domain (graph ML, anomaly discovery, NLP for KYC, etc.).

Qualifications

Education: Bachelor’s or Master's in Computer Science, Data Science, Engineering, or relevant field. Expertise: 3–5 years of expertise in AI/ML engineering, ideally in Financial technology, banking, or payments.

Specialized abilities:

• In-depth understanding of statistics, hypothesis running test, and classical ML algorithms.
• Robust programming competencies in Python (Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow).
• Competence in resources which includes Jupyter Notebooks and in data visualization libraries e.g Matplotlib and Seaborn.
• Expertise with SQL and practical understanding of big data resources (Spark, Dask, or similar).
• Practical experience deploying ML models through APIs, Docker, or cloud channels (e.g AWS/GCP/Azure/Huawei).
• Understanding with instantaneous operational structures (Kafka, NATS, or streaming pipelines) will be an added advantage.
• Expertise in fraud discovery, anomaly discovery, or credit risk models in financial technology.
• Expertise with process orchestration resources which includes Prefect or Airflow is a plus.
• Expertise in legal adherence frameworks (e.g. PCI DSS, NDPR etc.).

Interpersonal abilities:

• Robust issue resolution and logical mentality.
• Capability to operate in a dynamic new venture environment.
• Articulate professional and partner with cross-operational teams.

Nice to Possess:

• Exposure to MLOps resources (MLflow, Kubeflow, or SageMaker).
• Expertise in AI Orchestration structure (e.g. LangChain, Haystack).
• Expertise with AI/Automatic control resources which includes n8n and Zapier.