Data Scientist

• Python AWS / Azure LLM
  
• 
  
• ( / / )
  

• 
  
• /
  
• 
  
• 
  
• OSS
  
• 
  
• 
  

• AI AI AI
  

• In this position you will be required to understand issues while working with internal and external stakeholders and to design and implement solutions that utilize data science and machine learning technology. Development will mainly be done using Python deployment and operation will be performed using cloud environments such as AWS / Azure and the latest technologies such as LLM (largescale language model) will be actively adopted
  
• Since there is a lot of collaboration with the product development team as a machine learning engineer you will be involved not only in model construction work but also in software development work
  
• In addition there are many opportunities to collaborate with teams in other fields (natural language processing / optimization / image) to achieve multimodal support
  

• The main job will be project work for clients. The scale of the projects can be large or small butwe will work with business members to understand the customer plan and execute technical initiatives
  
• The technology will be related to data science / machine learning but if you have knowledge or interest in software development and operation we will be involved
  
• Understanding the customer also includes checking the data that the other party has but you may also be asked to make proposals on how to acquire data in the future
  
• You will consider the appropriate way to handle data for each project and work with stakeholders such as customers and business members to carry out engineering to achieve the projects goals
  
• Engineering is required to be done efficiently using external services such as OSS and the cloud as well as inhouse developed products
  
• It is also desirable to select and develop technology with operations in mind but if operational requirements have not been determined you will solidify them to the extent possible
  
• Outside of project work you may also be involved in accumulating internal technological assets and developing products.
  

• AI optimizes transactions with multiple electricity markets based on supply and demand and prices. Optimization of power generation plans at hydroelectric power plants using AI. Breast cancer observation research using wearable devices. Joint development of dietary management AI services
  

Requirements

• 
  
• AWS Azure
  
• GitHub
  
• 
  

• Tech Lead
  
• AI Responsible AI
  
• 
  
• 
  
• 
  
• 
  

• Experience in development work using data science
  
• Experience developing systems using cloud services such as AWS and Azure
  
• Experience in team development using GitHub
  
• Business level or higher Japanese language ability
  

• Experience leading other members as a tech lead
  
• Experience related to "Responsible AI"
  
• Experience related to demand forecasting recommendation systems and numerical simulations
  
• Wide knowledge and understanding of machine learning Bayesian modeling and statistical causal inference
  
• Experience presenting at academic conferences and writing papers
  
• Experience as a researcher
  

• Python AWS / Azure LLM
  
• 
  
• ( / / )
  

• 
  
• /
  
• 
  
• 
  
• OSS
  
• 
  
• 
  

• AI AI AI
  

• In this position, you will be required to understand issues while working with internal and external stakeholders, and to design and implement solutions that utilize data science and machine learning technology. Development will mainly be done using Python, deployment and operation will be performed using cloud environments such as AWS / Azure, and the latest technologies such as LLM (large-scale language model) will be actively adopted
  
• Since there is a lot of collaboration with the product development team, as a machine learning engineer, you will be involved not only in model construction work but also in software development work
  
• In addition, there are many opportunities to collaborate with teams in other fields (natural language processing / optimization / image) to achieve multi-modal support
  

• The main job will be project work for clients. The scale of the projects can be large or small, butwe will work with business members to understand the customer, plan and execute technical initiatives
  
• The technology will be related to data science / machine learning, but if you have knowledge or interest in software development and operation, we will be involved
  
• Understanding the customer also includes checking the data that the other party has, but you may also be asked to make proposals on how to acquire data in the future
  
• You will consider the appropriate way to handle data for each project, and work with stakeholders such as customers and business members to carry out engineering to achieve the project's goals
  
• Engineering is required to be done efficiently using external services such as OSS and the cloud, as well as in-house developed products
  
• It is also desirable to select and develop technology with operations in mind, but if operational requirements have not been determined, you will solidify them to the extent possible
  
• Outside of project work, you may also be involved in accumulating internal technological assets and developing products.
  

• AI optimizes transactions with multiple electricity markets based on supply and demand and prices. Optimization of power generation plans at hydroelectric power plants using AI. Breast cancer observation research using wearable devices. Joint development of dietary management AI services
  

Requirements

• 
  
• AWS Azure
  
• GitHub
  
• 
  

• Tech Lead
  
• AI Responsible AI
  
• 
  
• 
  
• 
  
• 
  

• Experience in development work using data science
  
• Experience developing systems using cloud services such as AWS and Azure
  
• Experience in team development using GitHub
  
• Business level or higher Japanese language ability
  

• Experience leading other members as a tech lead
  
• Experience related to "Responsible AI"
  
• Experience related to demand forecasting, recommendation systems, and numerical simulations
  
• Wide knowledge and understanding of machine learning, Bayesian modeling, and statistical causal inference
  
• Experience presenting at academic conferences and writing papers
  
• Experience as a researcher