Job Description

Who says Data Scientists can't fly planes?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.ResponsibilitiesAt KeepFlying, Data Scientists are the real deal. They work closely with the CTO, Product Director and a select group of Customer SMEs to build the brains behind the next-generation data platform and scale the offering across the Aviation Ecosystem. Day to day activities would be Diving deep into the big datasets and prepare them for model building and training Design and build efficient and scalable deep learning and machine learning algorithms Committing tested, documented, and reviewed code on a frequent basis, ideally daily. Code reviews and automated testing are core to our quality approach. Collaborating effectively with various stakeholders such as Product Director, Front end UI/UX team, and data engineers. Deep architectural understanding of good SaaS deployment patterns, and the technical options available from the various Cloud providers such as AWS or Azure. Contributing to team's innovation and IP creation.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.RequirementsDo you like to implement purposive and interesting probabilistic models? For success at KeepFlying all you need is: Experience in Exploratory Data Analysis including wrangling, grooming, transformation, and analysis. Experience applying statistical methods to solve data problems Excellent In-depth analysis of user data, mining the optimization space of product experience and recommendation strategies, and producing executable data insights. Experience with the automated build process (continuous integration) and source code version control tools (GITHub). Proven development experience using libraries such as Pandas, Koalas, etc. Experience with Microservice Architecture technologies and/or implementations. Hands-on experience in at least one of the following Python testing frameworks: unit test or py test. Must have AWS Lambda/Azure Functions, Batch, Serverless, ECR experiences.Why KeepFlyingKeepFlying 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.. Fast growing and well-funded start up. Standout Product - Be a part of first of its kind solution offered in the Aviation Industry.. Learning - You will learn from a group of proven leaders and innovators.. Flexibility - Our engineers enjoy the utmost flexibility as we believe in judging by the output and not by the hours worked.. Innovative mind-set - Our ecosystem gives an ample opportunity to showcase your enterprising &innovative ideas, knowledge and skills that directly contribute to the success of our company.We are backed by Marquee Investors and Industry Experts. Join us on our data to dollar journey with a kickass and fun team.
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Job Detail

  • Job Id
    JD1126154
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    Singapore, Singapore
  • Education
    Not mentioned