Scientist, Data at Stanbic IBTC

Job Description

• The Data Scientist will drive the design, development, adoption, and deployment of advanced analytics and AI solutions across all business units in the bank.
• The role will be responsible for collaborating with a team of data scientists in developing AI/ML models at scale, ensuring model governance and regulatory compliance, and supporting business units to embed AI into products, processes, and decision-making.
• The ideal candidate is both a strong technical leader and a strategic business partner.
• Support the development and execution of the bank’s Data Science & AI strategy in alignment with strategic business goals.
• Coordinate a team of data scientists and machine learning/AI developers in driving AI implementation across business and operations..
• Collaborate with senior business leaders to identify high-impact and emerging AI opportunities to gain a competitive edge.
• Oversee end-to-end delivery of machine learning models: data sourcing, feature engineering, model development, evaluation, deployment, and monitoring.
• Work closely with Data Engineering to ensure high-quality datasets for modeling.
• Ensure all models comply with internal model risk guidelines, CBN requirements, and global best practices.
• Stay updated with global AI trends, tools, and frameworks (GenAI, LLMs, RAG, agents, reinforcement learning).
• Lead Proof of Concept (PoC) and pilot initiatives for new AI capabilities.

Qualifications

• Bachelor’s Degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
• Master’s Degree and/or professional certifications (e.g., Azure ML, AWS ML, TensorFlow, Databricks, SAS, Agent orchestration, Microsoft Fabrics) can be an advantage.

Experience:

• 6–8 years of experience in Data Science, Artificial Intelligence, or Machine Learning.
• Minimum 3 years in a senior technical role.
• Experience in banking or financial services is strongly preferred.
• Proven track record of training and deploying ML and AI models to production at scale.
• Demonstrated experience with cloud platforms (particularly Microsoft Azure) and modern ML/AI tooling.

Additional Information:
Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Developing Expertise
• Documenting Facts
• Embracing Change
• Interpreting Data
• Managing Tasks.

Technical Competencies:

• Big Data Frameworks and Tools
• Data Engineering
• Data Integrity
• IT Knowledge
• Stakeholder Management (IT).