Data Scientist, Recognition

Nihonbashi, Tokyo

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Posted 2 weeks ago

COMPANYToyota Research Institute - Advanced Development (TRI-AD) was established in March 2018 as a $2.8 billion joint venture between Toyota Motor Corporation (TMC), Aisin Seiki Co., Ltd. (Aisin), and Denso Corporation (Denso) to develop fully-integrated, production-quality software and automated driving technology.  TRI-AD is headquartered in Tokyo, Japan and aims to create a smooth software pipeline from research to commercialization, and strengthen the collaboration within the Toyota Group in the domains of research and advanced development.  The core mission of TRI-AD is to become a world-class software and technology company, and to build the safest car in the world.  Attracting top talent internationally, TRI-AD has adopted English as its official language in order to facilitate collaboration and partnerships globally.
TEAMOur mission is to create world-class software and build the safest car in the world. As a data scientist on the Automated Driving Recognition team, you will help create a scalable data infrastructure and pipelines to support the development of a perception stack that is deployed to millions of users. Also, you will provide support in analyzing and improving machine learning model performance from a data perspective. 
WHO ARE WE LOOKING FOR?The ideal candidate is self-motivated to find solutions to complex real-world problems, and make an impact while contributing to a cross-functional team. You will combine cutting-edge technology with robust safety standards, and support a host of different projects within automated driving.

RESPONSIBILITIES

  • 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

MINIMUM QUALIFICATIONS

  • Master’s Degree in a quantitative discipline, e.g. statistics, math, or computer science, electrical engineering, or similar field of study
  • 3+ years of work experience in data science, machine learning, data engineering, or related areas
  • Extensive experience with statistical data analysis and data science tools
  • Experience writing software in Python or C++
  • Technical leadership and domain expertise to drive cross-functional research collaborations
  • Business-level Proficiency in English

PREFERRED QUALIFICATIONS

  • Ph.D. education in related field
  • Knowledge of Deep Learning models and techniques
  • Experience with multiple database and data architecture paradigms, such as Hadoop, MongoDB, Spark, SQL, Druid, Pachyderm
  • Experience with infrastructure and CI pipelines, such as Docker, Kubernetes, Airflow, Jenkins, Beam, Cyclone, MLflow
  • Passion for Technology and Mobility & possess excellent communication skills
If you are currently located at outside of Japan, don't worry, we'll set an interview over Google Hangout Meet or Skype.
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Job tags: Airflow Deep Learning Engineering Hadoop Kubernetes Machine Learning ML MongoDB Python Research Spark SQL