Senior Data Science Manager

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.
  

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