Data Scientist

Role PurposeThe Data Scientist will develop advanced models and analytics to unlock value from our client’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.
Contract – 12 months (high potential to extend further)Location – HeathrowHybrid – 2 to 3 days onsitePay – Flexible daily rate (inside IR35)Key Responsibilities

Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploration data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modeling. Continuously improving models based on feedback and operational performance. Develop models and analytics that can be generalised and adapted for different OpCos without extensive rework.

Required Skills & ExperienceProficiency in Python and ML frameworks (TensorFlow, PyTorch).Strong statistical and analytical skills.Experience with a wide range of Data Science techniques ( ML, Optimisation, Simulation, GenAI, etc.).Demonstrated ability to take models from design through to production deployment, including performance optimisation, 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.Initial co-location with client’s teams in London is essential to ensure close collaboration.Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment.Preferred Consulting-LevelpetenciesAbility to frameplex 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 oues and driving stakeholder satisfaction from day one.Experience in building reusable AIponents and frameworks for enterprise-scale deployments.