Data Science Engineer

About the Company

Accelya is a global leader in airline software, supporting over 200 airlines worldwide with an open, modular platform that enables modern airline retailing. The FLX ONE platform supports airlines across Offer, Order, Settlement, and Delivery (OOSD), aligned with IATA standards for modern retailing. Built on a cloud-native AWS infrastructure and backed by more than 40 years of airline industry expertise, Accelya helps airlines modernise operations, improve customer experience, and scale with confidence.

About the Role

As a Data Science Engineer, you will focus on building data-driven intelligence that informs decisions across FLX ONE Cargo. This role sits at the intersection of data science and software engineering—designing models and analytics that are not only accurate, but deployable, observable, and useful in production. You will work closely with product, engineering, and AI teams to turn raw operational and commercial data into predictive insights and decision-support capabilities that improve cargo outcomes.

Responsibilities

• Model Development & Analytics
• Design, implement, and validate machine learning and statistical models to support pricing, capacity planning, forecasting, and operational decisions.
• Translate business and operational questions into measurable data problems.
• Continuously evaluate and improve model performance using real-world data.
• Production Integration
• Work with engineers to integrate data science models into production services via clean APIs.
• Ensure models are versioned, testable, and suitable for cloud-native deployment.
• Support incremental rollout and safe adoption of data-driven capabilities.
• Data Engineering & Quality
• Work with structured and semi-structured datasets from multiple internal and external sources.
• Ensure data pipelines, features, and datasets are reliable, traceable, and well-understood.
• Contribute to data quality checks and monitoring.
• Measurement & Validation
• Define evaluation frameworks, experiments, and success metrics for models and analytics.
• Support A / B testing or controlled rollouts where appropriate.
• Communicate results and trade-offs clearly to technical and non-technical stakeholders.
• Collaboration
• Collaborate closely with AI Engineers to align modelling approaches with AI-enabled capabilities.
• Partner with Product and Engineering to ensure insights translate into real platform value.
• Participate in reviews and discussions that shape how data is used across Cargo

Qualifications

Required Skills

Preferred Skills