楽天グループ株式会社：1029346　Data Scientist – Measurement & Insight Section, Analytics Data Engineering Department (ADED)

非公開

東京都

会社名

楽天グループ株式会社

会社概要

未来を信じ、より良い明日を創っていく。
イノベーションを通じて、人々と社会をエンパワーメントする。私たちは、そんな想いを大切に世界の人々に喜びと楽しさを届けます。
楽天は、E コマース、FinTech、デジタルコンテンツ、通信など、70 を超えるサービスを展開し、世界10 億以上のユーザーに利用されています。
これら様々なサービスを、楽天会員を中心としたメンバーシップを軸に有機的に結び付け、他にはない独自の「楽天エコシステム」を形成しています。ダイバーシティ推進は、楽天にとって最優先の企業戦略のひとつです。従業員の出身は70カ国・地域以上。世界中からユニークで多様な文化的背景や視点を持つ優秀な人材が集まり、イノベーションの原動力になっています。社内カフェテリアにはベジタリアン、ハラル対応のメニューを用意。礼拝所（Prayer room）もあります。
また、仕事と育児の両立支援や、障がい者雇用・活躍促進も積極的に推進。社内のLGBT（※1）当事者やアライ（※2）に対して、情報共有やサポート体制の強化も進めています。誰もが自分らしく力を最大限発揮して働ける。それが楽天のダイバーシティです。

70を超えるサービスを提供し、世界30カ国にサービス展開拠点を持ち、従業員の出身国・地域数は100を超え、オープンポジション制度を活用して多様なキャリアを描くことができる点も魅力です。
フレックスタイム制度、事情に応じたリモートワークの活用が可能です。本社には託児所やフィットネスジム、三食無料で利用可能なカフェテリアが併設されるなど、社員を支える環境が整備されています。

ポジション

1029346　Data Scientist - Measurement & Insight Section, Analytics Data Engineering Department (ADED)

仕事内容

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 Hire
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.

求める経験・スキル

Mandatory Qualifications:

- Educational Background: Bachelor’s degree in Data Science, 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.