Job Title: Data Scientist – MRO AI Solutions
Job location: Harmondsworth, Middlesex
Duration: 6 Months
Description:
Role Purpose
The Data Scientist will develop advanced models and analytics to unlock value from BA’s operational data while ensuring solutions can be adapted for other OpCos. This role requires consultancy-level expertise in AI/ML and a strong ability to translate insights into business impact.
Key Responsibilities
- Design and implement predictive and prescriptive models for MRO AI Solutions.
- Perform exploratory data analysis and feature engineering.
- Collaborate with Data Engineers to ensure data readiness for modeling.
- Communicate findings and recommendations to business stakeholders.
- Continuously improve models based on feedback and operational performance.
- Develop models and analytics that can be generalized and adapted for different OpCos without extensive rework.
Required Skills & Experience
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch).
- Strong statistical and analytical skills.
- Experience with a wide range of Data Science techniques (e.g. ML, Optimisation, Simulation, GenAI, etc.).
- Demonstrated ability to take models from design through to production deployment, including performance optimization, monitoring, and integration into business workflows beyond proof-of-concept or prototype stages.
- Familiarity with airline operations or supply chain analytics is desirable.
- Significant experience in similar roles, with a proven ability to integrate quickly into new teams and deliver immediate value.
- Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment.
- Ability to frame complex problems and deliver actionable solutions.
- Strong presentation and storytelling skills for executive audiences.
- Experience in high-impact consulting or transformation projects.
- Track record of creating high-impact outcomes and driving stakeholder satisfaction from day one.
- Experience in building reusable AI components and frameworks for enterprise-scale deployments
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