Data Scientist ★Remote Work and Flextime★

【 About the company 】

With the mission of "Transforming the industrial structure with the power of technology," the company provides AI solutions and services to more than 150 companies to make AI easier to use.
In addition to model development, they also provide services that are most suitable for each company, from business feasibility testing to determine whether AI is worth the investment, and consideration of AI applications to support for production operations.
Especially for new business planning, they can make proposals and implement them as only they can, as the operator of the platform.

The company's platform is a service that minimizes the essential processes for development and operation so that customers can efficiently operate AI in production.
The full-scalable data warehouse and GPU environment are available as standard features, so you can use AI in production without the need to scale storage or develop learning environments such as GPUs.

Insight for Retail is a store analysis SaaS specialized for the retail distribution industry.
It analyzes data acquired from IoT devices such as network cameras and infrared sensors, and visualizes customer behavior from store visit to purchase as data, including number of visitors, number of people passing in front of the store, age and gender estimation, repeat customer estimation, and traffic line analysis.
It enables the verification of the effectiveness of a number of data-based measures in physical stores and contributes to the improvement of profits.

【 Job Description 】

You will be responsible for leading the technical aspects of the client's DX project. Specifically, you will work with consultants and project managers to provide practical solutions based on your technical knowledge and implement them.

■Lead the technical aspects of PoC and other projects.
・Propose appropriate technical solutions to client issues
・Mathematical modeling (prediction, optimization, statistical model design, etc.)
・Technical research through international conferences, papers, etc.
・Implementation of algorithms and logic, and evaluation of accuracy and performance
・Implementation of operational logic in the platform

■Horizontal deployment of technology and technology branding
・Generalization of implementation logic
・Disclosure of technical knowledge (speaking at workshops and meetups, writing tech blogs, etc.)

■Development environment
・Language: Python
・Environment used: GCP / AWS / Linux / Docker / Kubernetes / ABEJA Platform
・Libraries used: TensorFlow, Keras, PyTorch, Transformers, OpenCV, pandas, spaCy, LightGBM, etc.

■Members
・In Data Scientist, they have 3 Japanese, 1 French, 1 Indian, 1 Chinese, and 1 Malaysian, for a total of 7 people.

-----------------------------------------------------------------

【 Working time 】

10:00～19:00 (Flextime)

【 Welfare 】

Insurance: Health insurance, employee pension insurance, unemployment insurance, worker's compensation insurance
Health insurance: Enrolled in Kanto IT Software Health Insurance Association (can use directly managed recreational facilities, etc.)

Child allowance: 10,000 yen per month for each child up to the age of 20 with parental rights, starting after the trial period.
Health checkup: Conducted once a year for employees enrolled in health insurance.

【 Holidays 】

Full two-day weekends (Saturday and Sunday), national holidays
Annual paid vacations (10 days in the first year)
Others (congratulation, condolence, Golden Week, year-end and New Year holidays, child nursing, nursing care, etc.)

【Required】
※Experience leading the practical application of technology in the following areas (3+ years total)
Basic knowledge in machine learning or data analysis
At least 1 year of work experience related to the job description
Practical experience in exploratory data analysis
Ability to research international conferences, journal articles, and technical literature related to the job description
Experience in natural language processing (Japanese) or computer vision (DL, image processing systems) (not limited to practical work)
Machine learning marketing technology (recommendation, ad serving, etc.)
Comfortable with daily conversation and chatting in English

【Preferred】
Experience in operating machine learning applications
Experience in operating applications on Linux
Experience implementing applications that apply natural language processing (recommendation engine, sentence summarization engine, etc.)
Experience building infrastructure (AWS, GCP, Docker, etc.)
Skill in building development environment (various software installation, configuration, etc.)
Knowledge of SQL
Experience in handling databases (MySQL, Postgres, ORACLE, etc.)
Experience committing code to GitHub/uploading technical entries to blogs
Experience participating in competitions such as Kaggle
Business level English conversation