Lead Data Science and AI at Wema Bank Plc

Wema Bank Plc - Widely reputed as the longest surviving and most resilient indigenous bank in Nigeria, Wema Bank Plc has over the years, diligently offered a fully-fledged range of value-adding banking and financial advisory services to the Nigerian public.

We are recruiting to fill the position below:

Job Title: Lead Data Science and AI

Location: Lagos

Job Summary

• The Lead, Data Science and AI is responsible for providing strategic and technical leadership to the Data Science and AI team.
• The role oversees the end-to-end development and deployment of machine learning and artificial intelligence models to solve complex business problems and drive data-informed decision-making.

Job Details

• Provide technical leadership to the Data Science and AI team, mentoring team members and fostering continuous learning. 
• Supervise data scientists, assign tasks, review deliverables, and conduct performance appraisals. 
• Drive end-to-end development and deployment of ML models, ensuring alignment with business objectives. 
• Oversee data collection, cleaning, and preprocessing of structured and unstructured data for advanced analytics. 
• Lead the design and implementation of feature engineering pipelines to enhance model performance. 
• Manage the development of ML and AI models, including regression, classification, clustering, and deep learning, while ensuring scalability and accuracy. 
• Conduct advanced hyperparameter tuning, cross-validation, and model optimization techniques. 
• Collaborate with cross-functional teams to integrate ML solutions into production systems, ensuring seamless deployment and maintenance. 
• Manage the lifecycle of ML models, including versioning, retraining, and monitoring for performance.
• Guide the team in adapting and fine-tuning large language models (LLMs) for domainspecific use cases (e.g., chatbots, sentiment analysis, summarization). 
• Optimize ML/AI workloads using Azure Machine Learning (AML) and Azure AI services for cost and performance efficiency. 
• Implement and manage CI/CD pipelines for ML systems using Azure DevOps or other automation tools. 
• Act as a key liaison between data science, engineering, and business teams to prioritize high impact projects. 
• Develop strategies to address domain-specific challenges such as fraud detection, credit scoring, and personalized customer recommendations. 
• Translate complex business problems into technical deliverables and ensure timely project delivery

Qualifications and Skills
Below are qualifications and skills required to work as a Data Scientist Qualifications include:

• Bachelor’s degree in Engineering, Mathematics, Statistics, Computer Science, or related fields.
• Master’s degree in Data Science, AI, or a related field is a plus.
• Certifications in AI/ML or cloud platforms (e.g., Azure, AWS, GCP) are advantageous.

Skills:

• Programming: Proficiency in Python, R, or Scala.
• Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers.
• DevOps: 
• Experience with Git, Azure DevOps, or Jenkins.
• Cloud Platforms: Expertise in Azure AI/AML services and AWS, GCP etc
• Generative AI (LLMs)(Open AI, Gemini, Deepseek, etc) ,LangChain, Hugging Face Transformers, Prompt Engineering, Vector Databases (FAISS, Pinecone), Retrieval-Augmented Generation (RAG), and Azure OpenAI.

Education: 

• Bachelor’s or Master’s Degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 3+ years of professional experience in data science, analytics, or applied AI (preferably in banking or fintech). 
• Proven track record of developing and deploying machine learning models at scale.
• Solid understanding of financial services data (customer, credit, digital, and marketing analytics).
• Experience leading a technical team and managing multiple concurrent projects.

PrOFESSIONAL CoMPETENCIES 

• Proven expertise in AI/ML techniques, including traditional models (regression, classification, clustering) and advanced models (ensemble methods, neural networks, reinforcement learning). 
• Hands-on experience in feature engineering, ETL processes, and managing large-scale data pipelines. 
• Proficiency in cloud-based ML platforms, particularly Azure Machine Learning, Azure Data Lake, and Azure Kubernetes Service (AKS). 
• Strong knowledge of tools like MLFlow for model tracking, versioning, and lifecycle management. 
• Ability to interpret and present technical insights to non-technical stakeholders, driving datainformed decisions.
•  Deep understanding of domain-specific challenges and trends in banking (e.g., churn prediction, customer segmentation, fraud detection). 
• Advanced programming skills in Python (preferred), R, or Scala, and familiarity with frameworks like Scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers.
•  Experience with visualization tools ( Matplotlib, Seaborn) and databases (SQL, NoSQL, Azure Cosmos DB).
•  Oversee all existing production models.
• Expertise in leading technical teams, fostering innovation, and driving impactful data science projects.

Benefits

• Healthcare
• Staff Gym
• Creche
• Parental Leave (Paternity and Maternity)
• Year-End Bonus (13th month)
• Leave and Passage Allowance.

Application Closing Date
4th November, 2025.

How to Apply
Interested and qualified candidates should:
Click here to apply online