Recruitment, apply for Wema Bank recruitment 2025 below.
Gatekeepers News reports that Wema Bank Plc is 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.
Wema Bank Plc is seeking qualified candidates for the position below:
Lead Data Science and AI
Specifications:
- Full Time
- Required Qualifications: BA/BSC/HND
- Location: Lagos| Nigeria.
Description:
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 Requirements:
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.
QUALIFICATION 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.
Deadline: November 2, 2025
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