Applied Scientist Store Tech jobs at Amazon in Japan

Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Designing and implementing complex, scalable, and secure AWS solutions tailored to customer needs
2. Providing technical guidance and troubleshooting support throughout project delivery
3. Collaborating with stakeholders to gather requirements and propose effective migration strategies
4. Acting as a trusted advisor to customers on industry trends and emerging technologies
5. Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
About AWSDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- Bachelor’s degree required
- 10+ years of experience as a contact center technology architect, enterprise IT Architect or senior contact center developer working with leading contact center technology platforms and applications, such as Avaya, Cisco, Genesys, Verint, NICE, Salesforce, etc.
- Hands-on technical practitioner and individual contributor
- Hands-on experience working on the design, development and deployment of contact center solutions at scale

- Computer Science, Information Systems, or Engineering background preferred; Master’s degree desired
- 10+ years of experience building call center / collaboration / telephony platforms in a Cloud or On-Premises environment, particularly building application integration capabilities for CRM/ WFM platforms
- Professional Services or Consulting experience in highly-visible customer-facing roles
- Familiarity with Amazon Connect capabilities, benefits, and required deployment skills
- Visible IT Industry thought leadership on relevant topics related to enterprise IT call centers and infrastructure.
- Enterprise call center / telecomm implementation and operations experience
- Experience implementing and optimizing AI-powered customer service solutions
- Experience with AI/ML technologies in contact center applications, including Natural Language Understanding (NLU), Natural Language Processing (NLP), prompt engineering, large language model implementation, chatbot development and optimization, and AI/ML model training and fine-tuning
- Serverless development experience including complex integrations with Amazon Lex, Lambda, Kinesis, Dynamo DB, Bedrock and 3rd party AI services
- Software Development / DevOps experience with integrating contact center platforms, CRMs, and WFMs
- Use of AWS services in distributed environments with Microsoft, IBM, Citrix, VMware, Oracle, HP, etc.
- Strong verbal and written communication skills, with the ability to work effectively across internal and external organizations
- Responsibility for designing, implementing and operating contact centers or telecommunication infrastructures within an enterprise environment
- AWS Certified Machine Learning Engineer – Associate, AWS Certified Machine Learning - Specialty and/or AWS Certified AI Practitioner

GAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud.Key job responsibilities
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- Japanese fluency, Business English
- PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience, or Master’s degree plus 10 years of relevant work experience
- 5+ years of hands on experience with Python to build, train, and evaluate models
- 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high- performance computing
- 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques.
- Scientific publication track record at top-tier AI/ML/NLP conferences or journals
- Experience directly managing scientists or machine learning engineers

We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists.
Key job responsibilities
Specifically, the Research Scientist will:
• Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.
• Clean, analyze and select speech/language/other data to achieve goals
• Build and test models that elevate the customer experience
• Collaborate with colleagues from science, engineering and business backgrounds
• Present proposals and results in a clear manner backed by data and coupled with actionable conclusions
• Work with engineers to develop efficient data querying infrastructure for both offline and online use cases

- PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience in Python, Perl, or another scripting language
- Experience with various machine learning techniques and parameters that affect their performance
- Experience analyzing both experimental and observational data sets

ソリューションアーキテクトは、お客様訪問先で AWS を語るに相応しい人材であり、お客様のシニアクラスな方々（CxO レベルも含まれる）と議論した上でお客様のクラウド戦略に影響を与え、クラウド戦略・クラウドジャーニーをリードします。また一方で、技術的に確固たるバックグラウンドを持ち、お客様のアーキテクト及びソフトウェア開発者の方々と技術的な議論を交わし、実現可能性を顧客と共に確認しながら、クラウドを利用した既存システムの移行および新しいテクノロジーを活用したイノベーションをリードするポジションです。

- 1. Degree in Computer Science, Engineering, Mathematics, Technology, or a related scientific/technical field - OR - equivalent training, certifications, and/or experience, regardless of your academic background (0 -2 years)
- 2. Demonstrated ability to adapt to new technologies and learn quickly, even if you don't have prior experience
- 3. Knowledge and/or experiences in AWS services such as EC2, ALB, RDS, VPC, Route53, and S3
- 4. AWS Cloud Practitioner and/or Associate Solutions Architect and/or AI Practitioner Certificate

In this position, you will be expected to research, design and build/train/tune models and provide recommendations in areas including but not limited to natural language processing (automatic translation, summarization, extraction) and image processing (boundary detection, image understanding, image generation).
Key job responsibilities
As an Sr. Applied Scientist, your responsibilities will be:- Work closely with other Books scientists and engineers to build, review and improve your model design proposals.
- Keep up to date with scientific development in related field

- PhD, or Master's degree and 5+ years of building machine learning models for business application experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl

- PhD in computer vision, natural language processing or equivalent quantitative field
- PhD in engineering, technology, computer science, machine learning
- Business level Japanese language skills

急成長する組織で、データサイエンス・アルゴリズムのスキルを武器に物流に変革を起こしませんか？
アマゾンジャパン トランスポーテーション部門では、Applied Scientistとして、物流ネットワークの最適化・モニタリングに必要なAlgorithm/Heuristicモデル・ソリューションの構築を主導するSenior Applied Scientistを募集します。
Key job responsibilities
• 複雑でBusiness Impactの大きな課題に対するモデル・ソリューションを提供します。アーキテクチャレベルから設計し、必要に応じて他のエンジニアリングチームと協力して行います。
• Networkチーム専属かつ最初のScientistとして、前例のない取り組みに果敢に挑み、ステークホルダーと効果的に連携する必要があります。Tech・Biz両方のManagerとともにロードマップを確立し、ビジネスニーズを満たすソリューションを提供します。ドメインに対する学習意欲と、フルスタックサイエンティスト・エンジニアとして手を動かすことが必要になります。
• ネットワークオペレーション上の基準(正確性、効率性など)や運用上の基準(品質、一貫性、信頼性など)を確立するためのメカニズムをManagerとともに構築します。ユーザーであるネットワークチームに、分析結果を専門用語に頼ることなく効率的に伝えていく必要があります
• 戦略的に考え、トレードオフを行う必要があります。あなたの決定は、Amazonの物流ネットワークに大きな影響を与えます
• アイデアを効果的に伝える必要があり、あらゆるタイプのステークホルダーに対して口頭および文章で伝えることが出来ます。戦略的な文書から、作成したツールの使い方等といった運用上重要な文章まで、あらゆるスタックの文章を作成します。
• 限られたガイダンスの下で、プロジェクトをリードする必要があります。
As the dedicated and first Scientist for the Network team, you will boldly take on unprecedented initiatives and effectively engage with stakeholders. Work with both tech and business managers to establish a roadmap and deliver solutions that meet business needs. A strong learning appetite for the domain and ability to be a full-stack scientist/engineer are required.
Collaborate with managers to establish mechanisms that set network operation metrics (accuracy, efficiency, etc.) and operational standards (quality, consistency, reliability, etc.). You will need to efficiently communicate analysis results to the user network team without relying on specialized terminology.Ability to effectively communicate ideas, both verbally and in writing, to all types of stakeholders. You will produce content ranging from strategic documents to operational guides on using your developed tools across the stack.
Lead projects with limited guidance.A day in the life
• 10:00 出勤。自分がLeadしているプロジェクトのコードを書く
• 10:30 Data Engineerのの同僚が実装した新しい最適化ツールの説明を受ける。前から欲しかったBeam Search Bandwith Scheduler機能がついており感動
• 11:00 ネットワーク最適化シミュレーションのコードを設計。Notebookで実行し、午前中の仕事は終了
• 12:00 ランチ。今週の週替わりメニューのタンドリーチキンを初めて食べてみる。エキゾチック！
• 13:30 Scrum Daily Meeting。同僚の進捗を確認しつつ情報交換。シミュレーションの改良に別プロジェクトの知見が使えそう
• 14:00 Biz sideとフラッシュディスカッション。実装アイデアについて目線合わせ
• 14:30 肩が凝ったので会社でマッサージの施術を受ける。最高
• 15:00 一旦退社。残りは家で
• 16:00 シミュレーションの結果を確認。最適化エンジンはBayesでよさそうだけど、探索空間は要検討。いったん大域探索のために分散並列処理を書く
• 18:00 明日のProject Weeklyの準備。いくつかfigureを作成し、自分の進捗をNotebookに保存
• 18:30 コードレビュー。コメントをいくつか付けてApprove
• 19:30 お仕事終了About the team
弊チームはAlgorithm / Data Scienceソリューションを提供しており、主なミッションは以下の3つです。
• 1: 幹線輸送情報を包括的に管理・分析するための、大規模なData Martの改修・維持管理
• 2: 上記1のデータを利用した最適化・機械学習系アルゴリズムソリューションの提供
• 3: 上記1のデータを利用したBusiness Insight導出用のData Pipeline・Dashboardソリューションの提供
Overhauling and maintaining a large-scale Data Mart to comprehensively manage and analyze long-haul transportation data.Delivering optimization and machine learning-based algorithmic solutions utilizing the data from the above Data Mart.The machine learning-based solutions we have started providing just over a year ago have become a rapidly growing and highly anticipated area.

- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language

Key job responsibilities
As a Science Manager within JP AMZL LMEA team, you will lead a team of data and research scientists towards designing and deploying solutions that will likely draw from a large range of scientific areas such as supervised, semi-supervised unsupervised learning, reinforcement learning, advanced statistical modeling, optimization models and graph models. You will have an opportunity to be on the forefront of supply chain by working on some of the most difficult problems in the industry, with some of the best technical program managers, research scientists, data scientists, engineers, and economists to execute on JP AMZL Science vision and prepare scientific work for production systems integration. You will bring deep technical expertise in the area of Machine Learning and optimization. Other responsibilities include:* Lead a team of data and research scientists towards design, development and evaluation of highly innovative ML/optimization models for solving complex business problems.
* Technically lead and mentor the scientists on the team.
* Research and apply the latest ML techniques and best practices from both academia and industry.
* Use analytical techniques to create scalable solutions for business problems.
* Work closely with BI and data engineers to build relevant pipelines for your models at large scale.
* Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.A day in the life

- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- PhD
- Knowledge of machine learning approaches and algorithms
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations