Machine Learning/Data Scientist

Mission

NABLA Mobility Inc. is a startup driving operational optimization in the aviation industry through the development and provision of strategic network solutions powered by AI and machine learning (ML).

Despite advances in technology, decision-making in the aviation sector still heavily relies on manual processes and expert judgment. As a result, issues such as turbulence, traffic congestion, and delays continue to impact flight safety, operational efficiency, and environmental sustainability. We address these uncertainties by conducting advanced analyses of real-time and historical flight operation data.

Our solutions have already been adopted by multiple airlines and are actively used in daily operations.

The first is our flight optimization software, "Weave", a decision-support tool that quantitatively evaluates the trade-offs between reducing fuel consumption and minimizing flight time, while maintaining safety, to propose optimal strategic flight changes.

The second is "OBST", which semi-automates obstacle data processing. Based on NOTAMs and AIP information around airports, OBST quickly and easily evaluates the impact of obstacles and automates the takeoff performance calculation process, tailored to the specific operational conditions of each airline.

These solutions are powered by "Untangle", our suite of proprietary backend algorithms, including aircraft turbulence prediction models and route optimization engines for fuel efficiency. Through the Untangle API, we provide these algorithms in an API format, enabling seamless integration into airline systems.

Looking ahead, NABLA Mobility will continue to expand by incorporating the outcomes of our ongoing research and development. For example, one of our current research themes is the development of a flight delay forecasting model, which will further enhance operational resilience and efficiency.

As a pioneer in the industry, NABLA Mobility integrates cutting-edge academic theories, advanced technologies, and deep operational know-how to lead the future of global aviation.

Job Description

Key Responsibilities

• Lead the development and improvement of algorithmic models for 『Untangle』
• Explore the implementation of cutting-edge academic research to enhance algorithm performance
• Evaluate and improve algorithms and features based on real-world operational requirements

Current Tech Stack

• Backend: Python, TypeScript, Amazon API Gateway, AWS Lambda, Amazon DynamoDB,
• Frontend: Next.js, TypeScript,
• Infrastructure: AWS, Azure, Docker

Requirements

• Experience in Data Analysis:

-Hands-on experience analyzing real-world structured and unstructured data for problem-solving

-Proven ability to derive insights that lead to algorithm or model development

• Minimum 3 Years of Experience in at Least One of the Following Areas:

-Development of algorithms or machine learning models integrated into products or services

-Contribution to open-source libraries or widely used academic/research tools or systems

• Proficiency in standard tech stacks: Python, TypeScript, CSS, JavaScript, Ruby, C/C++, PostgreSQL, Docker, etc.
• Familiarity with AI/ML technologies using TensorFlow, PyTorch, or other deep learning libraries
• Experience with team-based development using Git / GitHub
• Proven Communication Skills:

-Ability to bridge between business and technical teams

• Educational Background:

-Master’s degree in Computer Science, Mathematics, Meteorology, Aeronautics, Space Science, Physics, or related fields

Preferred Qualifications

• Ability to incorporate raw product requirements into algorithm design
• Knowledge or expertise in aviation meteorology, air traffic control, and flight trajectory prediction
• Experience in physics-informed machine learning models

Annual Salary

¥5M - ¥7.5M