Data Scientist (Emiratisation)

The Data Scientist contributes to Emirates SkyCargo business problems using data analysis, mathematical modelling and machine learning. The role turns complex questions into analytical work, tests hypotheses and helps stakeholders use evidence to improve decisions and operational or commercial outcomes.

Key Responsibilities

• Structure business questions into measurable data-science problems and analytical plans.
• Clean, explore and model large datasets to identify useful patterns and predictions.
• Develop, validate and explain machine-learning or statistical approaches appropriate to the problem.
• Work with business and technology teams to deliver analysis within agreed timelines.
• Document assumptions, methods, limitations and results so that work can be understood and reused.

Requirements and Qualifications

• Degree in data science, statistics, mathematics, computer science, engineering or a closely related field.
• Relevant experience applying analytics, statistical modelling or machine learning to business problems.
• Experience with programming and data analysis tools such as Python or SQL is beneficial.
• Meet the Emiratisation and any further vacancy-specific eligibility requirements.

Skills

• Quantitative reasoning and structured problem solving.
• Data preparation, model evaluation and analytical storytelling.
• Collaboration with business stakeholders and technical colleagues.
• Ownership, curiosity and careful handling of data.

Employment Details

Emiratisation opportunity in the SkyCargo environment. Specific tools, seniority and experience requirements should be confirmed in the application details. The role is based in Dubai, United Arab Emirates unless the recruitment team specifies another location. Salary, working hours, benefits and reporting arrangements depend on the employment terms for this vacancy and are not assumed here. Candidates should confirm any required licences, education, experience, language, nationality, medical fitness, shift availability or screening conditions before applying. Successful candidates should work collaboratively, follow documented standards, protect confidential information and raise safety, compliance or service concerns promptly. Responsibilities may evolve with operational demand and the needs of the assigned team.