Job Summary
We are seeking a highly skilled and motivated Data Scientist /
AI Engineer to join our growing Advanced Analytics and AI team within the Group
Chief Analytics Office. Our organization is a leading financial services
institution offering universal banking products and services across Africa. In
this fast-paced, high-impact environment, the successful candidate will play a
key role in the development, deployment, and operationalization of machine
learning (ML), artificial intelligence (AI), generative AI, and agentic AI
models.
You will also mentor junior data scientists, guiding them in model selection,
architecture design, and deployment strategies tailored to financial use cases
such as credit risk, fraud detection, customer engagement, and
personalization.
Responsibilities
Key
Responsibilities:
- Design,
develop, test, and deploy production-grade ML, AI, generative AI, and
agentic AI models.
- Design,
develop, test and deploy AI blueprints for reuse/ re-application across
multiple AI use cases.
- Develop
guardrails in accordance with group security and architecture
standards.
- Partner
with stakeholders across Business Units and Functions, e.g. Risk,
Compliance, to identify, design, develop, deploy and manage impactful
solutions.
- Translate
complex business problems into structured tasks and deploy models that
deliver measurable value.
- Ensure
all solutions adhere to enterprise Data and AI architecture, security,
governance, and AI/ML operationalization standards.
- Build
model pipelines using enterprise MLOps frameworks, ensuring auditability,
scalability, and performance in production.
- Monitor
and maintain model performance, re-training and optimizing as needed in
dynamic banking environments.
- Provide
technical guidance and mentoring to data scientists across the Group,
especially around model selection, experimentation protocols, and
deployment best practices.
- Stay
up to date with advancements in the field, including foundation models,
multi-agent systems, and AI governance frameworks.
Qualifications
- Proficiency
in Python and data science toolkits (e.g., Pandas, NumPy, Scikit-learn,
TensorFlow, PyTorch).
- Demonstrated
experience designing and implementing ML and AI use cases using leading
platforms such as Databricks, AWS Bedrock, or Amazon SageMaker.
- Hands-on
experience with vector databases (e.g., Open search, Pinecone, FAISS,
Milvus) for efficient similarity search and retrieval.
- Exposure
to AI orchestration frameworks like LangChain, LlamaIndex Weaviate
pipelines to build scalable, retrieval-augmented applications.
- Exposure
to Model Evaluation framework to check ML and AI use cases accuracy and
performance testing.
- Deep
understanding of classical ML as well as generative AI (e.g., LLMs, GANs,
VAEs) and agentic AI (e.g. autonomous agents, multi-agent
coordination).
- Strong
grasp of MLOps tools (e.g., MLflow, Kubeflow, Docker, Airflow, CI/CD) and
cloud platforms, services and models.
- Experience
deploying models in highly regulated environments, with strong attention
to model risk, explainability, and compliance.
- Solid
foundation in enterprise-grade data pipelines, governance, and
architecture principles.
- Excellent
interpersonal and communication skills, with the ability to explain
complex technical concepts to non-technical stakeholders.
- Proven
ability to work under pressure and manage competing priorities in a
fast-moving, business-critical environment.
Experience:
- Bachelor’s
or Master’s degree in Computer Science, Data Science, Statistics,
Engineering, or a related field (PhD a plus).
- 3-
5+ years of experience in applied data science or AI roles, preferably
within financial services or banking.
- Demonstrated
experience in designing and deploying AI/ML solutions into production,
including generative AI.
- Familiarity
with financial industry use cases such as credit scoring, fraud detection,
KYC, personalization, and regulatory compliance analytics.
- Experience
working within enterprise architecture and governance frameworks.
- Prior
experience collaborating with, mentoring or coaching data
scientists.
Education
- Bachelor’s
Degree: Information Technology
How to Apply