Background

Kenya Airways, the leading African airline flying to more African destinations than any other carrier, takes pride in being at the forefront of connecting Africa to the world and the World to Africa through its hub Nairobi Jomo Kenyatta International Airport.

Purpose

The Head, Data, Analytics and Artificial Intelligence (Head-DNA) is responsible for spearheading Kenya Airways (KQ) transformative initiatives in Data, Analytics and Artificial Intelligence (AI). As a key member of the leadership team, you will have the opportunity to drive innovation and create substantial business value through advanced data-informed strategies. Reporting to the Chief Information and Data Officer (CIDO), you will manage the strategic, technical and operational aspects of the Data, Analytics and Artificial Intelligence (DNA) department, recruit top talent, and contribute to KQ’s growth.

Responsibilities

• Collaborate with the Data Privacy Officer to ensure PII data management is classified and managed for legal compliance
• Articulate the current state of data management, future state, and gap analysis for the enterprise regarding its maturity and positioning with respect to peer organizations.
• Establish and enforce best practices for data governance, compliance, quality, and security across the organization.
• Oversee the design, development, and maintenance of scalable data pipelines and infrastructure.
• Ensure data quality, integrity, and security across all data systems.
• Drive the research, development, and deployment of AI and machine learning models to solve complex business problems.
• Ensure the successful integration of AI solutions into existing business processes and systems.
• Stay abreast of the latest advancements in AI and machine learning and evaluate their potential impact on the organization.
• Develop and implement the strategic vision for data analytics across the organization, ensuring alignment with business goals.
• Serve as the organization's subject matter expert on advanced statistical analysis, experimental design, and financial impact analysis.
• Guide the development and implementation of robust analytical methodologies and processes across the organization
• Drive investment and budget planning of USD 2,500,000
• In tandem with the development of the organizations data strategy, the Head-DNA is responsible for the development of a 3-to-5-year plan of required budget to achieve the mission and goals as presented in the strategic plan.
• Collaborate with all functions of the business to ensure data needs are addressed and the required data is modelled and available to analysts and end-users
• Negotiate and manage Service Level Agreements and support contracts with the various Data Science and Analytics service partners to ensure SLA targets are met.
• Foster the creation of a data-driven culture, related competencies and data literacy across the enterprise.
• Provide educational opportunities to the organization’s staff for understanding of Data Governance and Data Stewardship culture, roles and responsibilities.

Qualifications

• Bachelor’s degree in Statistics, Computer Science, Information Technology, Data Science, Engineering or any other related quantitative field. Master’s degree is plus.
• 7+ years of experience in data engineering, data science, and/or AI, with at least 5 years in a leadership role.
• Familiarity with AI research and development tools and platforms.
• Extensive experience with machine learning frameworks, generative AI technologies, and big data platforms.
• Strong understanding of data architecture, data governance, and data security best practices.
• Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud).
• Knowledge of programming languages such as Python, R, Java, and SQL.
• Experience in big data technologies (Redshift, S3, Databricks, Data lakes, Spark).
• Working experience in one of these tools Looker/Tableau/PowerBI.

• Collaborate with the Data Privacy Officer to ensure PII data management is classified and managed for legal compliance
• Articulate the current state of data management, future state, and gap analysis for the enterprise regarding its maturity and positioning with respect to peer organizations.
• Establish and enforce best practices for data governance, compliance, quality, and security across the organization.
• Oversee the design, development, and maintenance of scalable data pipelines and infrastructure.
• Ensure data quality, integrity, and security across all data systems.
• Drive the research, development, and deployment of AI and machine learning models to solve complex business problems.
• Ensure the successful integration of AI solutions into existing business processes and systems.
• Stay abreast of the latest advancements in AI and machine learning and evaluate their potential impact on the organization.
• Develop and implement the strategic vision for data analytics across the organization, ensuring alignment with business goals.
• Serve as the organization's subject matter expert on advanced statistical analysis, experimental design, and financial impact analysis.
• Guide the development and implementation of robust analytical methodologies and processes across the organization
• Drive investment and budget planning of USD 2,500,000
• In tandem with the development of the organizations data strategy, the Head-DNA is responsible for the development of a 3-to-5-year plan of required budget to achieve the mission and goals as presented in the strategic plan.
• Collaborate with all functions of the business to ensure data needs are addressed and the required data is modelled and available to analysts and end-users
• Negotiate and manage Service Level Agreements and support contracts with the various Data Science and Analytics service partners to ensure SLA targets are met.
• Foster the creation of a data-driven culture, related competencies and data literacy across the enterprise.
• Provide educational opportunities to the organization’s staff for understanding of Data Governance and Data Stewardship culture, roles and responsibilities.

• Strong analytical and problem-solving skills.
• Proven track record of successfully leading data science, data engineering and/or AI teams.
• Excellent leadership, communication, and interpersonal skills.
• An ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.

• Bachelor’s degree in Statistics, Computer Science, Information Technology, Data Science, Engineering or any other related quantitative field. Master’s degree is plus.
• 7+ years of experience in data engineering, data science, and/or AI, with at least 5 years in a leadership role.
• Familiarity with AI research and development tools and platforms.
• Extensive experience with machine learning frameworks, generative AI technologies, and big data platforms.
• Strong understanding of data architecture, data governance, and data security best practices.
• Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud).
• Knowledge of programming languages such as Python, R, Java, and SQL.
• Experience in big data technologies (Redshift, S3, Databricks, Data lakes, Spark).
• Working experience in one of these tools Looker/Tableau/PowerBI.