Data Scientist II
This role demands a seasoned data scientist to architect and deploy advanced analytics solutions that directly impact Air Arabia’s business outcomes, with a focus on mentoring junior team members and ensuring scalable, data-driven decision-making. The ideal candidate will bridge technical expertise with strategic business alignment, driving experimentation and modeling to optimize performance in a fast-paced aviation environment.
Skills required
About this role
Job Purpose
Responsible for owning and delivering complex data science solutions end-to-end, leveraging advanced modeling, experimentation, and analytics to drive business impact and data-driven decision-making. Ensures scalable and business-aligned outcomes, collaborates with cross-functional teams, and mentors junior data scientists to enhance team capability and performance.
Key Result Responsibilities
- Translate complex business challenges into scalable data science and machine learning solutions that deliver measurable business value.
- Own the end-to-end data science lifecycle, including problem definition, data exploration, experimentation, model development, validation, deployment, and monitoring.
- Design and implement advanced analytical, predictive, and machine learning models to address business requirements.
- Develop and optimize features, algorithms, and model performance to improve accuracy, efficiency, and business impact.
- Ensure solutions are scalable, reliable, and aligned with business objectives, governance standards, and best practices.
Key Result Responsibilities-Continued
- Collaborate with Data Engineering teams to define data requirements, improve data quality, and ensure the availability of reliable data assets.
- Partner with ML Engineering and Platform teams to support model deployment, integration, monitoring, and production performance.
- Mentor junior data scientists through technical guidance, code reviews, and knowledge sharing.
- Communicate insights and recommendations to stakeholders, enabling data-driven decision-making across the organization.
Qualifications (Academic, training, languages)
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field (or equivalent practical experience).
- Strong expertise in machine learning and statistical modeling
- Advanced experience in experimentation (A/B testing, hypothesis testing)
- Ability to work with large and complex datasets
- Strong coding and model optimization capabilities
- Strong understanding of production constraints and model lifecycle
- Familiarity with monitoring concepts and model performance tracking
- Ability to define data and deployment requirements and effectively coordinate with Data Engineering and ML Platform teams
Work Experience
- With 4-6 years of experience in data science or machine learning roles
- Experience selecting and designing appropriate modeling approaches
- Experience working with deployed models and iterative improvements
