About the job
About The Role
As a Cargo Data Analytics Officer, you will solve complex problems and build scalable models/algorithms that will be integrated into various tools or systems within Qatar Airways Cargo. You will integrate with key SPOCs within the departments to build value added solutions. You will be developing models and data driven solutions that add a material lift to principal performance metrics.
- You will be responsible to identify, verify, evaluate and validate hidden patterns in data across multiple systems, and present insights back to executive management/internal department SPOC to drive strategic improvement.
- You will design, develop and implement analytical techniques on large, complex structured and unstructured data sets to help business to make better decisions. You will implement and statistical and data mining techniques, for example, hypothesis testing, machine learning, deep learning and retrieval processes on a large amount of data to identify trends figures and other relevant information.
We are looking for a passionate, high energy individual who has an understanding of air transport logistics and have a passion for technologies around data. To be successful in this role you will need to be minimum Bachelor’s Degree qualified in related disciplines such as Computer Science, IT, Mathematics or Engineering, with at least 2 years of Data Analytics experience.
- Experience working as a Data Scientist within the airline/airline cargo/air freight/logistics industry would be ideal.
- You will need to have an advanced analytical certification and knowledge of cloud platforms such as AWS and Azure.
- You should have hands on experience developing models using statistical techniques.
- You will need to have an understanding of statistics, operations research, forecasting and optimization methods and an advanced level of understanding of IT related topics.
- You should be able to make recommendations on data infrastructure and database relationships and be able to use your programming skills (e.g. SQL, Python, R, Scala, Machine learning, and data visualization tools such as Tableau, Power Bi, Qlikview) during analysis, model design and deployment.