Data Scientist

About the role

Reporting to the Data Manager, the Data Scientist works in the Data Science & Analytics function of Kenya Airways. The role advises the business on the potential of data, provides new insights into the company's mission and builds solutions through advanced statistical analysis, data mining and data visualization to improve business performance.

Key responsibilities

• Build econometric and statistical models covering projections, classification, clustering, pattern analysis, sampling and simulations.
• Build the scientific and technical foundations of the Data, Analytics & AI department to support planned and ongoing data projects.
• Recommend improvements to the business based on deep understanding of the problem domain and its data assets, especially strategic initiatives and value-based programs.
• Run ad-hoc data mining and exploration on large datasets linked to business strategy.
• Generate actionable insights using predictive statistical models, segmentation analysis, customer profiling, survey design and data mining.
• Collaborate with colleagues to share findings with stakeholders and improve decision-making.
• Take part in project execution, keeping scope clear and delivering on time and to specification, and audit issues within the agreed timeframe.
• Maintain strong stakeholder communication, follow policies and procedures, and keep competency assessments and development plans up to date.

Required profile

• Bachelor's degree in Statistics, Mathematics, Computer Science, Machine Learning, Economics or another quantitative field; equivalent experience is also accepted.
• At least three years of experience in business analysis, informatics and business outcomes research in a fast-paced, complex setting.
• Experience in probability and statistics, time-series analysis or econometrics, and in machine learning methods such as linear regression and decision trees.
• Practical experience rolling out Generative AI and Agentic AI use cases is an added advantage.

Required skills

• In-depth knowledge of Python.
• Cloud data science platform such as AWS SageMaker.
• Substantial knowledge of big data platforms.
• Big Data, Data Science or Gen.AI certification from a recognized institution.