Senior Data Science Manager
Summary
Senior data science leader in Lagos who builds and manages a team of data scientists and ML engineers, sets the data science and AI strategy, and oversees production-grade ML delivery, model governance, and stakeholder engagement. Core focus: predictive modeling, generative AI, and cloud ML platforms like AWS SageMaker, Azure ML, and Vertex AI.
Role Overview
We are looking for a Senior Manager, Data Science to lead
our advanced analytics, machine learning, and AI capabilities. In this role,
you will build and lead a high-performing team of data scientists and machine
learning engineers, shape our data science strategy, and drive the development
of scalable, production-ready solutions that deliver real business value.
The ideal candidate brings deep technical expertise, strong
business judgment, and a track record of turning complex analytical challenges
into measurable outcomes.
Key Responsibilities
Leadership & Strategy
- Lead,
mentor, and grow a team of Data Scientists and Machine Learning Engineers.
- Define
and execute the organisation's Data Science and AI strategy in alignment
with business goals.
- Identify
opportunities to apply data science across revenue growth, operational
efficiency, risk management, and customer experience.
Data Science & AI Delivery
- Oversee
end-to-end development and deployment of ML and AI solutions.
- Ensure
models are scalable, reliable, and production-ready.
- Set
best practices for experimentation, model evaluation, monitoring, and
performance optimization.
- Drive
adoption of advanced techniques including predictive modelling, generative
AI, reinforcement learning, and real-time decisions.
Governance & Risk Management
- Establish
and maintain standards for model governance, explain-ability, fairness,
compliance, and ethical AI.
- Ensure
adherence to regulatory requirements and industry standards governing data
use and AI implementation.
- Oversee
model risk management and ongoing performance monitoring.
Stakeholder Engagement
- Partner
closely with Product, Engineering, Risk, Operations, and Business teams to
deliver high-impact data science initiatives.
- Translate
technical findings and recommendations into clear, actionable insights for
senior leadership and non-technical audiences.
- Champion
a data-driven culture across the organization.
Requirements
Educational Qualifications
Required
- Bachelor's
degree in Data Science, Statistics, Mathematics, Computer Science,
Engineering, or a related quantitative field.
Preferred
- Master's
degree or PhD in Machine Learning, Artificial Intelligence, Applied
Mathematics, Econometrics, Statistics, or a related discipline.
Experience & Skills
- 8–12
years of experience in Data Science, Machine Learning, AI, or Advanced
Analytics, with at least 3 years in a leadership or people management
role.
- Demonstrated
experience building, deploying, and managing production-grade AI/ML
solutions.
- Proven
ability to drive business outcomes through predictive analytics and
data-driven decision-making.
- Strong
understanding of the full model lifecycle — from data preparation and
development through to validation, deployment, monitoring, and continuous
improvement.
- Hands-on
experience with cloud-based ML platforms such as AWS SageMaker, Azure
Machine Learning, or Google Vertex AI.
- Experience
in Financial Services, Fin-tech, Banking, Telecommunications, or other
data-intensive industries is an advantage.
- Strong
stakeholder management and cross-functional collaboration skills.
Preferred Certifications
- AWS
Certified Machine Learning – Specialty
- Microsoft
Certified: Azure AI Fundamentals
- TensorFlow
Developer Certification
- Other
relevant AI, ML, or Data Science certifications