Employment Opportunities at Kenya Airways

Purpose

Reporting to the Manager – Analytics, the Data Analyst serves as an analytics specialist in the business, focusing on the management of data from various sources and providing data-driven insights to relevant departments.

Responsibilities

• Analyses business data to provide the business’s management, heads, and stakeholders with information that supports departmental as well as overall business objectives
• Identify, analyze, and interpret trends and patterns in complex data sets, drawing insights that will aid the business in developing a suitable course of action.
• Audit system data to guarantee compliance, accuracy, and duplication management.
• Collaborate with business analysts to identify process automation opportunities and functions that will streamline current and future data management and reporting for the business
• 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.

Skills

• 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.

Qualifications

• A bachelor’s degree in business management, computer science, information management, or related field.
• Any IT management certification, such as ITIL, will be an added advantage.
• Experience with Power BI is strongly preferred.
• Proficiency with Excel, SQL and statistical methods (Python an added plus)
• At least 3 (three) years of relevant, data-related business experience in a busy/commercial environment. The candidate must also have had a proven and successful understanding of how to interpret a business’ needs and how to draw these needs from analysis or raw information and data.
• Demonstrate skill in SQL as well as proven skills and experience working with at least one other major databases platform for example, DB2, Oracle, Postgres, etc.

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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.

Responsibilities

• 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.

Skills

• 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.

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.

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Purpose

Reporting to the Senior Manager Data Science & Analytics, the Data Engineer is responsible for documenting data models, architecting distributed systems, creating reliable data pipelines, combining data sources, architecting data stores, and collaborating with the data science teams to build the right solutions for them.

Responsibilities

• Assisting in quality control of quantitative and qualitative research projects.
• Designing, building and support data processing pipelines to transform data using Cloud technologies e.g. AWS, Azure, GCP etc.
• Working with business analysts to understand business requirements and use cases.
• Developing and executing quality assurance and test scripts.
• Building survey and voter file data pipelines.
• Designing, building data assets in cloud solutions and/or oracle ODI.
• Designing and developing tools for internal team use to simplify complex task flows.
• Designing schemas, data models and data architecture for cloud environments.
• Implementing data flow scripts using Unix and/or scripting.
• Creating scripts and workflows to automate repeated data processing tasks.
• Working with data team to identify opportunities for task automation and helpful tools.

Skills

• Ability to work across regional teams with strong communication and collaboration skills
• Tendency to go above and beyond to make things work; manage own and others work to meet the deadline and assist other team members in their deliverables
• Ability to identify solutions and make the complex simple.
• Ability to breakdown complex problems into simple solutions

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Actuarial Science, Information Systems, Economics, Statistics, or a related quantitative field.
• Experience and knowledge of coding language such as Python.
• Good experience and knowledge of the SQL query language.
• Understanding of star schemas and data warehouse concepts.
• Knowledge of AWS/Azure tools and technologies
• Beneficial - ETL and ELT experience - both batch and microservices-led.
• Minimum three (3) years’ experience in a data engineer role or similar.
• Experience with data pipeline and workflow management tools: Airflow, etc.