Data Scientist, Recognition

at Woven Planet
Published November 21, 2022
Location Tokyo, Japan
Category Data Science  
Job Type Full-time  


Woven Planet is building mobility for a safer, happier and sustainable world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all.
For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today. Now, we are looking to the next 100 years and to extending that dream for a better life for all people from cars to smart cities.
Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. The complementary strengths enable us to optimize safety, advance clean energy and elevate well-being.  We envision a human-centered future where world-class technology solutions expand global access to mobility, amplify the capabilities of drivers, and empower humanity to thrive.
Woven Core develops, implements and scales human-centered automated driving solutions for personal and commercial use. Our team is responsible for developing perception technologies and its production software for the AD/ADAS system. To realize a fully reliable and highly functional system, we are tackling complex real-world problems utilizing large scale data, machine learning algorithms, and a variety of perception technologies.
The ideal candidate is self-motivated to find solutions to complex real-world problems, and makes an impact while contributing to a cross-functional team. You will combine cutting-edge technologies with robust safety standards while also considering cost efficiency. Also, you have patience to tackle the processes required for production development and approach them by asking “What can I do for you?” with a “Giver” mindset.


    • Design and continuously improve large scale iterative labeling, training, validation, and deploying data processing pipelines for machine learning that ingests cameras, LiDARs, radars, and other modalities
    • Develop and integrate data handling APIs, automation systems and tools to provide ground truth for machine learning and simulation
    • Analyze large scale data via statistical methods and identify its characteristics to propose technical solutions to ML engineers from a data perspective
    • Lead continuous improvement of the development environment via modern approaches from a data scientist perspective
    • Drive actions at scale to provide high impact services for Automated Driving Recognition Team scientifically-based methods and decision making and driving a high performance gain
    • Partner with engineering and product teams to solve business and technology problems using scientific approaches


    • Come up with data strategies on how to collect, sample, label, handle, and utilize tons of data from the market, test vehicles, and simulators to efficiently improve machine learning model performance of the perception stack for camera images that is deployed to millions of privately owned vehicles.
    • Design and continuously improve the scalable data pipelines and automation for machine learning and performance evaluation
    • Analyze large scale data and identify its characteristics to propose technical solutions for machine learning and performance evaluation
    • Lead data-related activities within the team, Woven Planet and in collaboration with Toyota group companies, as well as enhancing team members’ capability for data science.


    • Bachelor's degree in science or engineering
    • 3+ years experience in data science or related areas
    • Strong understanding of theoretical aspects of data science like machine learning (deep learning, statistical analysis, and  mathematical modeling
    • Strong experience in writing software in Python for data science, using SQL (or another type) database, and AWS services
    • Business-level proficiency in English


    • Ph.D. in Education or master’s degree in a related field
    • 5+ years experience in data science or related areas
    • 2+ years of tech lead or management experience in data science or related areas for business applications, such as production, commercial service, or public service development
    • Experience in analyzing huge (e.g. peta byte) scale database
    • Experience in developing perception related technologies, such as camera image processing, computer vision, machine learning, or deep learning
    • Experience in modeling and deploying machine learning models for business applications
    • Experience in designing data annotation rules for machine learning
    • Experience in building or managing infrastructure, such as Docker, Kubernetes, Jenkins, GitHub Actions
    • Experience in working in the automotive industry (especially, AD/ADAS field)
    • Experience in working in a huge scale (>100 engineers) project as tech lead or manager for a part of that
    • Business-level proficiency in Japanese (especially, smooth reading and listening)
If you are currently located at outside of Japan, don't worry, we'll set an interview over Google Hangout Meet or Skype.
・Competitive Salary - Based on skills and experience
・Work Hours - Flexible working time with NO core-hours
・Paid Holiday - 20 days per year (prorated)
・Sick Leave - 6 days per year (prorated)
・Holiday - Sat & Sun, Japanese National Holidays, and other days defined by the company
・Japanese Social Security - all applicable (Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance)
・In-house Training Program (software study/language study)
By submitting your application you agree to the following terms:
・We are an equal opportunity employer and value diversity.
・We pledge that any information we receive from candidates will be used ONLY for the purpose of hiring assessment.