|This posting is managed by:||United World Inc|
|Company Name||Company is not publicly visible|
IT (Other) - Data Analyst/Data Scientist
Asia Japan Tokyo
You will be in charge of the following tasks related to their own SaaS product that solves the inventory problem.
・Development and management of various indicators
・Construction of prediction model by machine learning
■ Technology stack
・Development language: Python
・DB: Redshift, Aurora (PostgreSQL compatible)
・Infrastructure: Amazon Web Services
・AWS products: ECS, S3, Step Functions, Lambda
・Machine learning tools: Kedro, MLflow
・Tools: GitHub, Slack, CircleCI, Sentry
Founded in 2012, it is a venture company that develops SaaS products that solve the problem of excess inventory with an approach using statistics and AI. The product is equipped with services such as future sales forecasts and purchase trend analysis, and supports retail companies such as apparel to maintain their business without having to carry a lot of excess inventory that is supposed to be disposed of. By approaching the inventory problem, they aim to realize a world where companies don't make things which are not in need, and to grow further as a company that contributes to solving global problems such as mass production, mass disposal, labor environment, and environmental pollution.
[Attractive points of company/work]
It is a product that can provide a completely new solution to the inventory problem that has been neglected for decades as a fateful problem in the industry.
Since the service launch, they have received a lot of feedback, and the number of introductions is increasing rapidly.
<Example of product functions>
・Listing of products that can be sold properly, which will be useufl for controling discounts
・Automatic creation of charts of various indicators to check the health of the business
・Creating a list of products that will contribute to increasing the average spend per customer, etc.
|Working Hours||9:00～18:00 *Remote work available|
one of the following
・Experience working as a data scientist, starting from problem setting for analysis
・Experience in model development in Python
・Experience in model development and data analysis using table data
・Japanese language proficiency（Business level)
one of the following
・Knowledge of time-series data analysis methods
・Basic understanding of statistics and machine learning
・Experience trying to solve business problems by applying machine learning
|Japanese Level||Business Level(JLPT Level 2 or N2)|
|Salary||JPY - Japanese Yen JPY 6000K - JPY 10000K|
Commuting/ Transportation Allowance