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

Reporting to the Data Manager. Data Science & Analytics, the Data Scientist is responsible for advising the business on the potential of data, to provide new insights into the business’s mission, and by advanced statistical analysis, data mining, and data visualization techniques, to create solutions that enable enhanced business performance.

Qualifications

Bachelor’s degree in Statistics, Mathematics, Computer Science, Machine Learning, Economics, or any other related quantitative field. Working experience of the equivalent is also acceptable for this position.

Big Data, Data Science or Gen.AI certification from recognized institutions.

At least three (3) years of working experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting. Practical experience in rolling out Gen. AI and Agentic AI use cases is an added advantage.

Experience working in probability and statistics, time-series analysis, or econometrics as well as experience in the use of machine learning methods, for example, linear regression, decision tress, and so forth.

Experience as well as in-depth knowledge of the Python programming language, Cloud data science platform e.g. AWS sage maker and substantial knowledge of big data platforms.

• Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling and simulations.
• Build the foundation of state-of-the-art scientific and technical capabilities within the Data, Analytics & AI department to support several planned and ongoing data projects.
• Provide forward-thinking recommendations to the business by building in-depth understanding of the problem domain and available business data assets, especially those pertaining to strategic initiatives and value-based programs
• Execute ad-hoc data mining and exploration tasks on large datasets related to the business 'strategies.
• Generate actionable insights applying advanced statistical techniques, for example, predictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and data mining
• Collaborate with other data scientists to communicate obstacles and findings to relevant stakeholders to improve decision making and drive business performance.
• Be an advocate for a continually improving way of working within the team to drive efficient and impactful engagement and accurate delivery of service.
• 100% adherence to policies, procedures and statutory guidelines.
• Participate in project execution to ensure that projects scope is understood, completed on time, to service delivery specifications.
• Audit issues close within the quarter of identification, or within the agreed time frames, whichever is shorter.
• Strong relationships and communications with stakeholders to ensure customer satisfaction and that concerns are addressed and expectations met.
• Own up-to-date and actioned competency assessments and development plans.

• Ability to think creatively, highly driven and self-motivated
• Strategic perspective with an ability to analyze complex issues, develop appropriate action plans and deliver results.
• Ability to synthesize and analyze diverse data and information, develop and recommend strategies.

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Machine Learning, Economics, or any other related quantitative field. Working experience of the equivalent is also acceptable for this position.
• Big Data, Data Science or Gen.AI certification from recognized institutions.
• At least three (3) years of working experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting. Practical experience in rolling out Gen. AI and Agentic AI use cases is an added advantage.
• Experience working in probability and statistics, time-series analysis, or econometrics as well as experience in the use of machine learning methods, for example, linear regression, decision tress, and so forth.
• Experience as well as in-depth knowledge of the Python programming language, Cloud data science platform e.g. AWS sage maker and substantial knowledge of big data platforms.