Head of Data Science

What will you do?

The Head of Data Science will assist in defining, building and leading Sanlam's data science capability, driving innovation and insights across all business units within the Sanlam Life & Savings cluster. This role has a direct line to the Chief Data & Analytics Officer and is pivotal in harnessing data science capabilities to fuel our strategies for growth, client experience, and operational excellence. The successful candidate will be at the forefront of implementing cutting-edge data analytics, machine learning and AI solutions, all within cloud and on-premise modeling environments to solve complex business problems. 

Key Responsibilities 

• Strategic Leadership: Define and implement the data science strategy, with a strong emphasis on cloud-native modeling environments and MLOps, in alignment with Sanlam's business goals. 
• Innovation and Development: Spearhead the development of advanced analytics models in cloud-native environments for predictive analysis, client segmentation, and financial product optimization. Leverage MLOps practices to streamline model development, deployment, and monitoring. 
• Stakeholder Engagement: Collaborate with business leaders and IT departments to ensure seamless integration of data science solutions. Communicate complex data-driven insights to non-technical stakeholders. 
• Data Governance and Management: Ensure data integrity, security, and compliance within cloud environments and in adherence to data governance and MLOps practices. 
• Team Management and Development: Build a team skilled in cloud technologies, machine learning, and MLOps. Promote continuous learning and professional growth. 

What will make you successful in this role?

Requirements 

• Master's in Advanced Analytics, Data Science, Computer Science, Statistics, or a related field. 
• A minimum of 10 years of experience in data science, with at least 5 years in a leadership role, preferably within the financial services industry. 
• Demonstrated expertise in developing and deploying models in cloud-native environments, with a thorough understanding of cloud services (AWS, Azure, Google Cloud). 
• Strong background in MLOps practices, including continuous integration/continuous deployment (CI/CD) pipelines, containerization (Docker, Kubernetes), and model monitoring and management. 
• Proficiency in data science tools and programming languages such as Python, R, SQL, and big data technologies. 
• Familiarity with data governance, data ethics, and regulatory compliance. 
• Exceptional communication and interpersonal skills, with the ability to articulate complex data concepts to non-technical stakeholders. 

Personal Attributes 

• Strategic thinker with a problem-solving mindset. 
• Innovative, with a strong focus on leveraging cloud technologies and MLOps to stay ahead of industry trends. 
• Leadership qualities that inspire and motivate a team towards embracing cloud-native solutions and MLOps methodologies. 
• Excellent organizational and project management skills. 

Turnaround time

The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers. 

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