- The majority of the team starts working between 9 and 10.30am until You will have complete flexibility to determine your working hours as long as you are present for the meetings where your attendance is required.
- Number of working hours will be determined together with the hiring manager in case you want to pursue the Fellowship parttime. In case of fulltime, working hours will be 40/week as per a standard contract.
- Our office is located in Meguro, and presence in the office is required 3 times/week. You are free to work remotely for the remaining two days or come to the office if you prefer.
- Pythonに精通していること。
- Currently enrolled (any year) in a PhD course in a Japanese university, studying Machine Learning or related disciplines.
- Fluency in Python.
- Fluent in either Japanese or English.
- Published papers in peerreviewed international conferences and journals.
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Amazon Science Fellow, Japan Retail Science - Tokyo, 日本 - Amazon Japan G.K.
説明
日本の大学で機械学習や関連領域の研究に従事している学生の皆様に向けたフェローシッププログラムのご案内です。Amazon JapanのRetail Scienceチームでは、何百万人もの顧客にインパクトを与える価値あるテクノロジーに繋がるような、新しいプロトタイプやコンセプトを開発するプロジェクトに従事していただく学生を募集しています。プログラムは1ヶ月から3ヶ月の短期間のプロジェクトになります。プロジェクトの対象となるテーマには、自然言語処理、表現学習、レコメンデーションシステム、因果推論といった領域が含まれますが、これらに限定されるわけではありません。プロジェクトは、チームのシニアサイエンティスト1名または複数名のガイダンスのもとで定義、遂行され、プロジェクト中は他のサイエンティストもメンターとしてフォローします。
学生の皆様が新しいモデルを考案したり、新しいテクノロジーを活用し実験する時間を最大化できるようにすることが目標です。そのため、プロジェクトではエンジニアリングやスケーリングよりも、プロトタイピングを行い具体的に概念実証を行うことに集中します。
また、Amazonでは論文出版も推奨しています。従事した研究開発活動の成果物として出版される論文には著者として参加することになります。
フェローシッププログラムは目黒の東京オフィスで、他のチームと一緒に行われます。Amazonは、プログラム期間中に必要なIT機器(ラップトップなど)、給与と通勤費を支給します。
Are you a current PhD student enrolled in a Japanese university researching Statistics, Machine Learning, Economics, or a related discipline? The Japan Retail Science team is looking for Fellows for short term (1-3 months) projects to develop new prototypes and concepts that can then be translated into meaningful technologies impacting millions of customers.
In this position, you will be assigned a project to carry out from areas including but not limited to natural language processing, representation learning, recommender systems, or causal inference.
The project will be defined and carried out under the supervision of one or more of our senior scientists, and you will be assigned another scientist as a mentor to follow you during the project.
Our goal is to maximize the time you spend on inventing new models and experimenting with new techniques, so the work will concentrate on prototyping and creating a tangible proof of concept, rather than engineering and scaling.
The fellowship will be carried out from our Tokyo office in Meguro together with the rest of the team.
Amazon will provide the necessary IT equipment (laptop, etc.) for the duration of the fellowship, a salary, and commuting expenses.
A day in the life- チームの多くのメンバーは、午前9時くらいから10時半くらいまでの間に仕事を始め、夕方6時から7時には仕事を終えています。出席が必要なミーティングに参加していれば、勤務時間は自由に決められます。
- パートタイムを希望する場合、勤務時間数は採用担当者とともに決定します。フルタイムの場合、労働時間は通常の契約通り週40時間となります。
- オフィスは目黒にあり、週3回の出社が必要です。残りの2日間はリモートワーク、オフィスへの出勤いずれも可能です。
私たちのチームは、日本および世界のすべてのAmazonのベンダー企業に提供されるソリューションを支える製品を発明し、開発しています。私たちは、プロダクトマネージャーやビジネス関係者と協力し、科学的なモデルを開発し、インパクトのあるアプリケーションに繋げることで、Amazonのベンダー企業がより速く成長し、顧客により良いサービスを提供できるようにします。
私たちは、科学者同士のコラボレーションが重要であり、孤立した状態で仕事をしても、幸せなチームにはならないと考えています。私たちは、科学者が専門性を高め、最先端の技術についていけるよう、社内の仕組みを通じて継続的に学ぶことに重きを置いています。私たちの目標は、世界中のAmazonのベンダーソリューションの主要なサイエンスチームとなることです。
Our team invents and develops products powering the solutions offered to all Amazon vendors, in Japan and worldwide.
We interact with Product Managers and Business stakeholders to develop rigorous science models that are linked to impactful applications helping Amazon vendors grow faster and better serving their customers.
We place strong emphasis on continuous learning through internal mechanisms for our scientists to keep on growing their expertise and keep up with the state of the art.
Our goal is to be primary science team for vendor solutions in Amazon, worldwide.We are open to hiring candidates to work out of one of the following locations:
Tokyo, 13, JPN
BASIC QUALIFICATIONS
- 現在、日本の大学の修士課程または博士課程に在籍し、機械学習または関連分野を研究していること。年次は問いません。
- 査読付き国際会議・学術誌に論文を発表していること。
就業の場所における受動喫煙を防止するための措置に関する事項については、下記リンク先をご覧ください。
The salary information can be provided individually prior to the 1st interview
賃金に関する条件は、1次面接の前に個別にご案内することができます
