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Senior Data Scientist – Machine Learning & Aviation Data Solutions

SpringCube

Full time - Manager

Aerospace, Aviation & Airlines

Singapore ( Remote )

Published 4 weeks ago

Salary: SGD5,000 - SGD10,000

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Senior Data Scientist – Machine Learning & Aviation Data Solutions

Company Overview
A rapidly growing Aviation DSaaS (Data Science as a Service) platform is revolutionizing how Airlines, Lessors, Financiers, and OEMs assess the revenue potential of their assets. This platform bridges the gap between technical and engineering data with financial and risk data to model asset values and predict revenue over their remaining useful lives.

Job Description
As part of the pioneering data science team, the Senior Data Scientist will take full ownership of the platform’s entire recommendation pipeline. You will work on deep learning and machine learning algorithms, leveraging large datasets to extract meaningful insights that will help aviation companies simulate and forecast revenue potentials. If you have a passion for aviation and a solid background in Applied Math, Probability, and Computational Statistics, this role offers an exciting opportunity to drive the development of cutting-edge data science solutions in the aviation industry.

Key Responsibilities

  • Data Preparation: Dive deep into large datasets, preparing them for model building and training.
  • Algorithm Development: Design and build efficient, scalable deep learning and machine learning algorithms for the platform.
  • Code Quality: Write tested, documented, and reviewed code, committing to best practices like code reviews and automated testing.
  • Collaboration: Work closely with the CTO, Product Director, Front-end UI/UX teams, and data engineers to ensure seamless integration of models into the platform.
  • SaaS Deployment: Contribute to a deep architectural understanding of SaaS deployment patterns and cloud-based services (AWS, Azure).
  • Innovation Contribution: Play an active role in the team’s innovation and IP creation efforts, contributing to the growth of the platform.
  • Recommendation Pipeline Ownership: Own and oversee the development of the platform’s entire recommendation pipeline, collaborating across teams (Product, Business, Engineering) to ensure a robust solution.

Job Requirements

  • Experience in Data Science: Proficient in Exploratory Data Analysis (EDA), including wrangling, grooming, transformation, and analysis of large datasets.
  • Statistical Methods: Strong experience applying statistical methods to solve data problems and build predictive models.
  • Recommendation Systems: Expertise in user data analysis, mining product optimization spaces, and developing recommendation strategies.
  • Development & Testing: Experience with automated build processes (CI/CD) and version control tools (GitHub). Hands-on experience in Python testing frameworks (unit test, pytest).
  • Technical Skills: Experience with libraries such as Pandas, Koalas, and cloud technologies (AWS Lambda, Azure Functions, Serverless).
  • Microservices Architecture: Familiarity with microservice architecture technologies and implementations, ensuring scalability and reliability.

Preferred Qualifications

  • Cloud Experience: Hands-on experience with AWS Lambda, Azure Functions, Batch, ECR, and other cloud-based solutions.
  • Industry Passion: Passion for aviation and solving complex business problems in the aviation ecosystem.

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore during these challenging times.

  1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
  2. No Client Relationship: This company is not a client of SpringCube unless stated.
  3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
  4. No Liability: SpringCube is not liable for inaccuracies.