Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our team to solve complex air cargo logistics challenges using data science.
- Company: meshX is revolutionising data utilisation in the aviation industry with innovative AI solutions.
- Benefits: Enjoy a remote-first environment, flexible scheduling, and competitive salary with professional development opportunities.
- Why this job: Make a significant impact on aviation's digital transformation while working with cutting-edge technology.
- Qualifications: Advanced degree in Data Science or related field with 3+ years of relevant experience required.
- Other info: Submit your resume and examples of your data-driven projects in air cargo operations.
The predicted salary is between 43200 - 72000 £ per year.
About us
At meshX, we're dedicated to revolutionizing how companies harness their data. Our innovative platform makes AI accessible and integrates seamlessly with various tech stacks, transforming data into actionable insights and streamlining business operations.
About you
We're seeking an experienced Data Scientist with aviation industry knowledge to join our team, with specific expertise in cargo operations. You'll leverage our federated data platform to solve complex challenges in air cargo logistics, network optimization, capacity management, and operational efficiency. Your expertise will help our aviation clients transform their cargo operations data into actionable insights that drive operational excellence and strategic decision-making in the air freight sector.
What you bring to the table
- Advanced degree (MS or PhD) in Data Science, Statistics, Computer Science, Aerospace Engineering, or related field
- 3+ years of experience applying data science techniques to aviation industry problems
- Strong programming skills in Python, R, or similar languages for data analysis
- Experience with machine learning libraries and frameworks (scikit-learn, TensorFlow, PyTorch)
- Proficiency in SQL and experience working with large, complex datasets
- Knowledge of statistical analysis, experiment design, and modeling techniques
- Understanding of aviation operations, aircraft systems, or airline management
- Excellent data visualization skills and experience with tools like Tableau, Power BI, or Python visualization libraries
- Strong communication skills to present findings to both technical and non-technical stakeholders
Highly Desired Skills
- Experience with air cargo operations data sources (freight manifests, ULDs, cargo capacity, load factors)
- Knowledge of cargo-specific aviation regulations and compliance requirements (dangerous goods, customs)
- Background in cargo network optimization, load planning, or revenue management
- Experience with demand forecasting and capacity planning for air freight operations
- Familiarity with supply chain analytics and intermodal logistics optimization
- Understanding of cargo terminal operations and ground handling efficiency
- Experience with geospatial data analysis for route network and hub optimization
- Knowledge of cloud computing environments (AWS, Azure, GCP)
- Previous work with federated data architectures or data mesh approaches
You will be responsible for
- Develop advanced analytics models to address air cargo-specific challenges using our federated data platform
- Clean, transform and validate data from multiple aviation systems
- Create demand forecasting algorithms to optimize cargo capacity planning and yield management
- Design optimization models for cargo network efficiency, routing, and ULD utilization
- Build predictive models for identifying bottlenecks in cargo handling and terminal operations
- Analyze cargo performance data to identify revenue opportunities and operational inefficiencies
- Develop solutions for real-time cargo tracking, exception management, and proactive alerts
- Work with our platform engineers to develop cargo-specific features and capabilities
- Present findings and recommendations to clients in clear, actionable formats
- Stay current with emerging air cargo trends and data science techniques to drive innovation
What we offer
- Opportunity to work at the intersection of cutting-edge data science and aviation technology
- Remote-first environment with flexible scheduling
- Competitive salary and benefits package
- Access to advanced computing resources and data infrastructure
- Collaborative team of data scientists and domain experts
- Professional development opportunities and conference participation
- Chance to make significant impact on the aviation industry's digital transformation
How to Apply
Please submit your resume, a brief description of your experience applying data science in air cargo operations, and any relevant examples of projects or research you've conducted in this domain. We're particularly interested in hearing about how you've helped air freight organizations optimize their cargo operations through data-driven insights.
Data Scientist - Aviation Industry employer: JR United Kingdom
Contact Detail:
JR United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Aviation Industry
✨Tip Number 1
Familiarise yourself with the latest trends in air cargo operations and data science. This will not only help you understand the challenges faced by the industry but also allow you to speak knowledgeably during interviews, showcasing your passion and expertise.
✨Tip Number 2
Network with professionals in the aviation and data science fields. Attend industry conferences or webinars, and connect with people on platforms like LinkedIn. Building relationships can lead to valuable insights and potential referrals for the position at meshX.
✨Tip Number 3
Prepare to discuss specific projects where you've applied data science techniques to solve problems in the aviation sector. Be ready to explain your thought process, the tools you used, and the impact of your work on operational efficiency.
✨Tip Number 4
Showcase your programming skills by working on relevant projects or contributing to open-source initiatives. Highlighting your proficiency in Python, R, or SQL through practical examples can set you apart from other candidates.
We think you need these skills to ace Data Scientist - Aviation Industry
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights your experience in data science specifically within the aviation industry. Emphasise your skills in cargo operations, programming languages like Python or R, and any relevant machine learning frameworks you've used.
Craft a Compelling Experience Description: In your application, include a brief description of your experience applying data science in air cargo operations. Be specific about the projects you've worked on and how they contributed to optimising cargo operations.
Showcase Relevant Projects: Include examples of projects or research that demonstrate your ability to solve complex challenges in air cargo logistics. Highlight any predictive models or optimisation algorithms you developed and their impact on operational efficiency.
Communicate Clearly: When presenting your findings or recommendations in your application, ensure that you communicate them in a clear and actionable format. This will show your ability to convey complex data insights to both technical and non-technical stakeholders.
How to prepare for a job interview at JR United Kingdom
✨Showcase Your Aviation Knowledge
Make sure to highlight your understanding of the aviation industry, particularly in cargo operations. Be prepared to discuss specific challenges you've faced and how your data science skills helped address them.
✨Demonstrate Technical Proficiency
Be ready to talk about your programming skills in Python or R, and your experience with machine learning libraries. Consider bringing examples of projects where you applied these skills, especially in relation to air cargo logistics.
✨Prepare for Data-Driven Discussions
Expect to discuss how you've used data analysis to drive operational efficiency. Prepare to explain your approach to cleaning, transforming, and validating data from multiple sources, as well as any predictive models you've developed.
✨Communicate Clearly
Since you'll be presenting findings to both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Use visual aids if possible, and be ready to answer questions about your insights and recommendations.
