Data Scientist Team Lead – (AI Engineer Lead)

Job Purpose At Emirates Group our Analytics Centre of Excellence (ACoE) is a centralized unit that provides data and analytics support to Emirates Group businesses. This allows our businesses to make better decisions by using data and analytics to understand our customers, operations, and markets.The ACoE is an essential part of Emirates Group's digital transformation strategy. The unit is helping Emirates Group to become a more data-driven organization and to make better decisions by using data and analytics. As a Data Scientist Team Lead you will manage and drive data science projects through the application of mathematical modelling, machine learning, problem structuring and big data analysis to solve complex business problems across the Emirates Group portfolio. The role will require strong skills in computer science, mathematics, statistics and creative problem solving. The job holder is a focused individual who is able to transcend the world of theory, bring it to life in the business context and collaborate successfully with cross functional teams including academic researchers, business stakeholders and information technology teams. In this role you will: - Manage team of Data Scientists, ensuring the culture, strategy and vision are passed to the teams. Aligned with the DS and EA leadership, review team capabilities and establish training/mentoring plan. - Support and drive DS execution within team, targeting and developing relationships with the key internal stakeholders and clients to continue to drive practice demand growth. - Derive business insight from large, structured, semi-structured and unstructured, data sets and work with business stakeholders to deploy insights derived from this analysis to extract commercial value. - Develop, formulate and execute big data models to solve complex business problems. Research, design, implement and validate cutting-edge algorithms to achieve targeted business outcomes using mathematical models, machine learning, operational research theories and dynamic simulations. - Build prescriptive models to identify multi-dimensional trends and patterns to understand our customers, optimise revenue and demand management plus drive efficiencies across the operational environment including aircraft operations, engineering, workforce management and catering. - Work with cross-functional team members, combining computer science and mathematics, to identify and inject high-value actionable insights into business processes at their point of highest impact. Work in quick iterations, using the techniques and algorithms best suited for solving the challenging problems of the aviation business. - Develop and recommend enhancements to existing tools with the goal of advancing the data science capabilities of the organisation. Perform validation and testing of models to ensure adequacy and reformulate models as necessary. - Clearly document and communicate the outcomes of the data science initiatives and make sure that the insights and findings can be clearly understood by business stakeholders and translated into actions. - Inspire and promote the adoption of advanced analytics and data science across the entirety of our organization and provide expertise on mathematical concepts for the broader applied analytics team. Qualification To be considered for the role, you must meet the below requirements: Qualifications: - MSc/PhD in a relevant field such as data science, operations research, mathematics, science, data mining, artificial intelligence, applied statistics, machine learning or economics. Experience: - 7-10+ years of hands-on experience in the Analytics ecosystem including: - - Experience Managing Data Science or Analytics Teams or acting as Manager in a consulting company. - 3-5 years hands-on experience with big data technologies (Spark and Hadoop ecosystem) and deep learning frameworks (Tensorflow, Keras, etc.). - 5-7 years hands-on experience with SQL, R, Python. - 2-4 years hands-on experience with DevOps frameworks (Git, CI/CD, Docker). - 3-5 years hands-on experience building libraries and packages to be re-used by others. - 3-5 years hands-on experience building DS Solutions for production usage. - Team player with a problem-solving attitude. - Experience of leading & delivering advanced analytical projects to large, complex organisations in a multi-functional environment. - Able to challenge and review the quality and value generated from analytical output. - Focus on driving business value for business clients to support long term relationships. Ability to grow teams, ensuring the culture and strategy gets followed by the new hires. - Join us in a management role and enjoy an attractive tax-free salary. On top of our generous travel benefits, including discounted flights and hotel stays around the world, this managerial role also has an excellent leave and healthcare package. That’s on top of transport benefits, life insurance and more. Salary

MSc/PhD in data science, operations research, mathematics, science, data mining, artificial intelligence, applied statistics, machine learning or economics. 7-10+ years of hands-on experience in the analytics ecosystem. Experience managing data science or analytics teams or acting as a manager in a consulting environment. 3-5 years hands-on experience with big data technologies (Spark and Hadoop ecosystem) and deep learning frameworks (TensorFlow, Keras, etc.). 5-7 years hands-on experience with SQL, R, Python. 2-4 years hands-on experience with DevOps frameworks (Git, CI/CD, Docker). 3-5 years hands-on experience building libraries and packages for reuse. 3-5 years hands-on experience building data science solutions for production usage. Ability to lead and deliver advanced analytics projects in large, multi-functional organizations. Strong focus on driving business value and leadership to grow teams.

- Manage a team of Data Scientists, aligning culture, strategy and vision; assess capabilities and establish training/mentoring plans. - Drive DS execution with key internal stakeholders and clients to grow practice demand. - Derive business insight from large structured, semi-structured and unstructured datasets and deploy insights to extract commercial value. - Develop, formulate and execute big data models; research, design, implement and validate cutting-edge algorithms using mathematical models, machine learning, operations research and dynamic simulations. - Build prescriptive models to identify multi-dimensional trends, optimize revenue and demand management, and drive efficiencies across aviation operations and related functions. - Collaborate with cross-functional teams to inject high-value insights into business processes; iterate quickly using appropriate techniques and algorithms. - Enhance existing tools to advance data science capabilities; validate and refine models. - Document and communicate outcomes clearly to business stakeholders and translate findings into action. - Inspire adoption of advanced analytics across the organization and provide expertise in mathematical concepts to the broader team.