Being part of the pioneer batch of data science hire, you will have to take full ownership of platform’s entire recommendation pipeline.
KeepFlying® is an Aviation DSaaS (Data Science as a Service) platform which will serve Airlines, Lessors, Financiers & OEMs simulate revenue potential of their assets using financial and risk models. KeepFlying® will bridge the gap between Technical & Engineering data with that of Finance & Risk data to help value assets and their expected revenue potentials over their remaining useful lives. We are looking for candidates who have a passion for aviation and a strong background in Applied Math, Probability, and Computational Statistics. They must be comfortable working with large sources of unstructured data to extract meaningful insights and collaborate with the Aviation ecosystem to solve important business cases as the industry recovers from the pandemic. Our team is rapidly expanding to meet the needs of our accelerating growth, and we are looking for self motivated individuals to help us deliver this first of its kind DSaaS platform to our Aviation clients all over the world. To be successful in this role, you must be able to work closely and flourish with a smart pride of young talents in a dynamic workplace that want to release incredible solutions in a timely, efficient, and scalable way.
At KeepFlying®, Data Scientists are the real deal. Theywork closely with the CTO, Product Director and a select group of Customer SMEsto build the brains behind the next-generation data platform and scale theoffering across the Aviation Ecosystem. Day to day activities would be
Being part of the pioneer batch of data science hire, you will have to take full ownership of platform’s entire recommendation pipeline, focus on working with various teams (Product, Business, Engineering) who are best in the field.
Do you like to implement purposive and interestingprobabilistic models? For success at KeepFlying® all you need is:
We are looking for a skilled data engineer who has expertise in developing and architecting data pipelines.