My main role is to build the pipeline and infrastructure for data collection and I collect unstructured data on the internet cleanse it model it and make it available for products. All data collection systems are frameworkbased and instead of creating them from scratch each time I have built a system where data cleansing and modeling run automatically just by combining input and output
Recently the size of data has increased and the data engineering team is building data platforms and introducing distributed systems to conduct analysis so if you wish you can also get involved in the fields of data analytics and science. We are particularly focused on the use of LLM and there are projects to verify how LLM can be used to process difficult unstructured data
:
:
TypeScript React
Storybook jest
Amplify
Frontend:
Language: TypeScript React
Library: Storybook jest
Hosting: Amplify
:
AWS ElasticBeanstalk
DB Aurora ElasticSearch
Node.js Python
Express
DataDog
AWS Lambda AWS Batch AWS API GateWay AWS Glue
Server side:
Infrastructure: AWS ElasticBeanstalk
DB: Aurora ElasticSearch
Language: Node.js Python
Framework: Express
Monitoring: DataDog
Other: AWS Lambda AWS Batch AWS API GateWay AWS Glue
:
OpenAI
Amazon Bedrock
OpenSearch
SageMaker
Athena
Glue
Requirements
:
ETL
MYSQL MongoDB
:
OSS
Tableau Power BI D3.js
OpenAI LLM
Required Skills:
Web sing experience
Data cleansing experience
Data modeling experience
ETL experience
Experience with databases (MYSQL MongoDB)
Experience in extracting data from unstructured data
Business level English
Welcome Skills:
Natural Language Processing Machine Learning
Streaming processing experience
Experience in building and operating data platforms
Development experience outside of work OSS activities etc.
Native Japanese
Experience using data visualization tools (Tableau Power BI D3.js etc.)
Experience using LLM products such as OpenAI
Roles and Responsibilities:
0
LLM LLM
My main role is to build the pipeline and infrastructure for data collection, and I collect unstructured data on the internet, cleanse it, model it, and make it available for products. All data collection systems are framework-based, and instead of creating them from scratch each time, I have built a system where data cleansing and modeling run automatically just by combining input and output
Recently, the size of data has increased, and the data engineering team is building data platforms and introducing distributed systems to conduct analysis, so if you wish, you can also get involved in the fields of data analytics and science. We are particularly focused on the use of LLM, and there are projects to verify how LLM can be used to process difficult unstructured data
:
[ ]:
TypeScript, React
Storybook, jest
Amplify
[Frontend]:
Language: TypeScript, React
Library: Storybook, jest
Hosting: Amplify
[ ]:
AWS, ElasticBeanstalk
DB Aurora, ElasticSearch
Node.js, Python
Express
DataDog
AWS Lambda, AWS Batch, AWS API GateWay, AWS Glue
[Server side]:
Infrastructure: AWS, ElasticBeanstalk
DB: Aurora, ElasticSearch
Language: Node.js, Python
Framework: Express
Monitoring: DataDog
Other: AWS Lambda, AWS Batch, AWS API GateWay, AWS Glue
[ ]:
OpenAI
Amazon Bedrock
OpenSearch
SageMaker
Athena
Glue
Requirements
:
ETL
MYSQL MongoDB
:
OSS
Tableau Power BI D3.js
OpenAI LLM
Required Skills:
Web sing experience
Data cleansing experience
Data modeling experience
ETL experience
Experience with databases (MYSQL, MongoDB)
Experience in extracting data from unstructured data
Business level English
Welcome Skills:
Natural Language Processing, Machine Learning
Streaming processing experience
Experience in building and operating data platforms
Development experience outside of work, OSS activities, etc.
Native Japanese
Experience using data visualization tools (Tableau, Power BI, D3.js, etc.)
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