Data Scientist - Measurement & Insight Section, Analytics Data Engineering Department (ADED) job opportunity at Rakuten International.

Home Jobs In Japan Tag: Analytics Data Engineering Department (ADED) Data Scientist - Measurement & Insight Section, Analytics Data Engineering Department (ADED) position at Rakuten International


DateMore Than 30 Days Ago bot
Rakuten International Data Scientist - Measurement & Insight Section, Analytics Data Engineering Department (ADED)
Experience: 7-years
Pattern: full-time
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Analytics Data Engineering Department (ADED)

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loacation Tokyo, Japan, Japan
loacation Tokyo, Japan....Japan

Job Description: Business Overview   Rakuten Group has almost 100 million customer bases in Japan and 1 billion globally as well, providing more than 70 services in a variety such as e-commerce, payment services, financial services, telecommunication, media, sports, etc.     Department Overview   Following the strategic vision “Rakuten as a data-driven membership company ”, we, Analytics Data Engineering Department (ADED), are expanding our AI & data business across our multiple Rakuten Group companies.   The team under Measurement & Insight Section leverages advanced technology to craft bespoke, intelligent systems that elevate personalized user experiences and drive strategic efficiency across Rakuten's various applications and services.     Position :   Why We H ire   We are looking for an experienced Data Scientist who will contribute to: 1) extracting actionable insights from data and   2) the model development for Rakuten’s data & AI products at scale, which deliver personalized experiences   　   Position Details   The Data Scientist will be instrumental in transforming complex business requirements into prototype solutions, conducting exploratory data analysis, and model building (Note that successful candidates may also be involved in designing robust & scalable data/training pipelines but not mandatory).   The section is also hiring a Machine Learning Engineer – its focus is more on software engineering for production applications. 　   Work Environment   Our Tech Stack   While we advocate for using the right technology for the right task, we often leverage the following technologies .   Python, Django, Flask, Golang, REST, GraphQL , Docker, Kubernetes, Helm, Argo Workflow, Argo CD, Gitlab (CI), Sentry, Presto/Trino, Hive, Hadoop, Spark, Postgres, SQL/HQL, Kubeflow, etc.   Team   An international and diverse team with highly skilled engineers.   Mandatory Qualifications :   - Educational Background: Bachelor’s degree in Da ta S cience , Machine Learning, Computer Science, Physics. - At least around 7 year+ of professional experience or the equivalent skills.   - Mathematics, Statistics, or a similar quantitative field. Mathematical understanding of general statistical modeling, machine learning algorithms, and data analysis techniques. - Proficiency in using at least one of modern ML frameworks such as TensorFlow, PyTorch , or Keras , etc.   　   Desired Qualifications :   - High level understanding of modern MLOps trends.   - Expert/Senior level in at least one of the major/modern computer languages including but not limited to Python, C/C++, Java, or Go, etc.   - Experience in full lifecycle in production development: from (large scale) data pipelines to model training, inference APIs (both batch and real-time), and model version control & tracking/observability, including overall solution design optimizations. 　 # engineer  # datascientist  # AI #aianddatadiv Languages: English (Overall - 3 - Advanced)

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