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.