Engineering Technologies Data Scientist

We are currently seeking a talented and data-driven Engineering Technologies Data Scientist (EngTech Data Scientist) to join our Airline Engineering team. This new role is based within our busy Head Office (with hybrid working) at Leeds Bradford International Airport and is part of the overall Engineering Technologies & Predictive Analytics Team.

What will you do in the role?
As an Engineering Technologies Data Scientist, you will be responsible for analysing complex datasets, developing predictive models and providing data-driven insights to drive innovation within our engineering and maintenance operations. You will play a critical role in the execution of the engineering data and analytics strategy and the development of advanced analytics and data-driven strategies.
You will:

• Develop and implement predictive analytics models to forecast aircraft maintenance needs and optimise operations.
• Collaborate with cross-functional teams to identify opportunities for data-driven improvements in safety, efficiency, and cost management.
• Design and implement data collection, processing, and analysis frameworks, ensuring data integrity and accuracy.
• Work closely with IT and Data teams to integrate advanced analytics tools with existing systems, facilitating seamless data flow and utilisation.
• Communicate complex data findings to non-technical stakeholders through clear and impactful reports and visualisations.
• Stay current with the latest trends and technologies in data science and engineering analytics, applying new methodologies where applicable.

What are the key skills / experience you’ll already have?
We are looking for a talented data scientist with a passion for applying advanced analytics to engineering challenges.
You will:

• Possess a strong background in data science, with experience in Python and PySpark for data processing.
• Exposure to ML Frameworks like Scikit Learn/TensorFlow/PyTorch
• Experience with Palantir Foundry and its applications, including Code Workbook, Contour, Code Repositories, and Data Lineage, is desired but not essential.
• Have experience in data preprocessing, feature engineering, and model evaluation.
• Be an excellent communicator, able to convey complex information clearly to a diverse audience.
• Demonstrate strong problem-solving skills and the ability to work effectively in a fast-paced environment.
• Have a deep understanding of data analytics technologies and an eagerness to explore new tools and techniques.
• Be knowledgeable about aerospace / airline engineering and maintenance principles (preferred but not required).
• Have a track record of delivering impactful data science projects in a business or engineering context.