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The company
Harnham have partnered with a reputable client within the aviation industry who is looking to innovate their Data Science capabilities. This is a pivotal role in ensuring operational efficiency and optimizing resource allocation within their maintenance teams.
The role
This position offers the opportunity to develop a model for optimizing aircraft maintenance operations while aircraft are on stand. Currently, maintenance tasks are manually assigned, leading to inefficiencies and wasted time. The proposed model will automate work planning by:
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Collecting and structuring relevant data
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Creating optimized work plans for engineering teams
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Assigning the right engineers with the required skills for each aircraft
Your experience
The role will be embedded within a dedicated team, consisting of one senior and one junior data scientist. The organization employs Data IQ as an end-to-end MLOps tool to streamline low-code data preparation and model building. Additionally, collaboration with architecture teams will be essential. A prototype model is already in place, and the objective is to complete full development and testing by April.
Technical Requirements
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Strong expertise in SQL and optimization models
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Python proficiency (preferred but not essential)
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Experience in developing and deploying data science solutions (essential)
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Ability to engage with commercial teams to ensure practical implementation
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Strong stakeholder engagement skills to drive adoption and usability
Logistics The role is based within our Data Science team and will report directly to senior leadership. The successful candidate will have a clear mandate to drive efficiency, capitalize on data-driven insights, and ensure operational excellence within aircraft maintenance.
I'd love you to apply if you are passionate about using data science to solve complex logistical challenges and drive meaningful business impact.
