Group Executive: Data Science

**Role Purpose**

The Data Science & Analytics team is responsible for driving the company's data-driven initiatives, leveraging advanced analytics, and harnessing the power of AI/ML/DL technologies to address business needs. They play a vital role in managing the company's data assets, including data governance, analytics, and business intelligence, to extract valuable insights and support informed decision-making. The team collects and analyses large volumes of data from various sources, building machine learning and deep learning tools to derive actionable intelligence. Collaborating with stakeholders across the organization, they identify key data sources, develop robust data pipelines, and create analytical frameworks to extract insights from Big Data. They ensure data quality and accuracy through proper formatting, cleaning, and handling of missing or incomplete data. Overall, the Data Science & Analytics team plays a critical role in effectively managing and utilizing Big Data to drive innovation, enhance operational efficiency, and support the development and deployment of AI models and algorithms.

**Role Description**

Envision, establish, and lead a Data Science and Analytics team to develop innovative solutions addressing business needs using AI/ML/DL technologies. Lead and manage a team of creative staff members, fostering their growth and development in building AI models and algorithms. Attract, train, and cultivate top-tier data science and AI talent, ensuring a strong team with specialized expertise.

Foster a high-performance culture within the team, encouraging achievement and recognizing excellence. Establish a robust framework for data analytics, ensuring proper collection, processing, and analysis of data to support the development and deployment of AI models and algorithms. Develop and execute a comprehensive strategy to build a strong data science and analytics team that advances the group's leadership and competitiveness through model building and data analysis.

Lead cross-functional projects utilizing advanced data modelling and analysis techniques to uncover insights, guide strategic decisions, and identify optimization opportunities. Build and maintain data models, reporting systems, automation systems, dashboards, and performance metrics that support key business decisions. Identify synergies and opportunities for leveraging data science and analytics across the organization. Oversee the design and delivery of reports and insights that analyse business functions, operations, and performance metrics.

Influence and provide guidance on strategic and technical decisions based on data analytics and BI dashboards to gain a competitive advantage for the group. Optimize processes for data intake, validation, mining, engineering, modelling, visualization, and communication to ensure efficient and effective data-driven deliverables. Analyse and interpret the results of analytical initiatives and effectively communicate insights to stakeholders in leadership, technology, sales, marketing, and product teams.

Organize and drive the successful completion of data insight initiatives, managing analysts and data employees, and fostering collaboration with stakeholders to achieve desired outcomes. Develop and maintain a data governance framework to ensure data quality, privacy, and compliance with regulations. Drive innovation by exploring and implementing new data science techniques, tools, and methodologies to enhance analytical capabilities.

Collaborate with business stakeholders to identify key performance indicators (KPIs) and metrics that align with strategic goals and monitor their progress. Foster a data-driven decision-making culture across the organization, promoting the use of data insights in decision-making processes. Measure the impact of data science and analytics initiatives on business performance, such as revenue growth, cost reduction, customer satisfaction, and operational efficiency. Establish and track data-driven goals and targets for the team, ensuring continuous improvement in data analytics capabilities and outcomes.

Develop and nurture partnerships with external data vendors, technology providers, and research institutions to access cutting-edge data and stay updated on industry trends. Lead data science and analytics projects with a focus on scalability and sustainability, ensuring solutions can be effectively implemented and maintained.

Monitor and optimize the performance of AI models and algorithms, measuring their accuracy, reliability, and effectiveness in achieving desired outcomes. Foster a culture of learning and development within the data science and analytics team, providing opportunities for skill enhancement and knowledge sharing. Act as a strategic advisor to senior leadership, providing insights and recommendations based on data analysis to drive business strategy and innovation.

Computer Science, Machine Learning, Data Science, Engineering or rel