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Senior Data Scientist, Japan Transportation Engineering & Analytics

Senior Data Scientist, Japan Transportation Engineering & Analytics

Amazon Japan G.K.Tokyo, JPN
30+ days ago
Job description

Data ScientistやData EngineerのチームをLeadし、Businessに必要な機械学習 / Heuristicモデル・ソリューションの構築を主導するSenior Data Scientistを募集します。

Eコマースモールを運営しています。「地球上で最もお客様を大切にする企業になること」を企業理念に掲げ、お客様が欲しい商品を欲しい時に最速のお届けでお買い物出来るようなネットワークの構築を行っています。遅延なく商品を入荷しお客様に幅広いセレクションを提供し、お約束通りに商品をお届けすることはサービスの根幹ですが、物流・小売業界を取り巻く環境は日々変化しています。常に変化する状況にあってもお客様のために常に高いサービス品質を提供することは、当社の競争力に必要不可欠な要素です。

Amazon Japanの成長に伴って拡大を続けるサプライチェーンは日々複雑性を増しており、Business Operationの効率化・可視化・意思決定の質の向上が求められています。AWSやAmazon 独自のToolを使って、これらのチャレンジに対して最適なモデル・ソリューションを提供するチームをリードするEngineerを募集しています。

Revolutionize logistics with your data science and algorithm skills in a rapidly growing organization.

The Amazon Japan Transportation division is seeking a Senior Data Scientist to lead a team of Data Scientists and Data Engineers, and spearhead the development of machine learning / heuristic model solutions that meet the business's needs. This is an exciting opportunity to contribute your talents.

Our company operates Japan's largest e-commerce marketplace. Guided by the vision of becoming "Earth's most customer-centric company," we are building a network that delivers the products customers want, when they want them, as quickly as possible. Seamlessly replenishing inventory and providing a wide selection are core to our service, but the logistics and retail landscape is constantly evolving. Maintaining high service quality amidst this change is essential to our competitiveness.

As Amazon Japan continues to grow, our expanding supply chain is becoming increasingly complex. There is a strong need to improve the efficiency, visibility, and quality of our business operations. We are seeking an engineer to lead a team that leverages AWS and Amazon's proprietary tools to deliver optimal model and technology solutions for these challenges.

Key job responsibilities

  • 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。
  • People Managementを除くTech Leading・Project Leading・Team Leadingを行います。Scrumプロセスに基づき、チームの優先順位を設定し、顧客やステークホルダーと効果的に連携する必要があります。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。
  • Managerとともに構築します。
  • Managerとともに定義します。
  • Provide model and technology solutions for complex, high-impact business challenges. Design these solutions from an architectural level, collaborating with other engineering teams as needed.
  • Serve as a Tech Lead, Project Lead and Team Lead (excluding people management). Based on Scrum processes, you will set team priorities, effectively liaise with customers and stakeholders. Partner with Managers to establish a roadmap and deliver solutions that meet business needs.
  • Collaborate with Managers to establish mechanisms that uphold engineering standards (e.g., accuracy, efficiency) and operational standards (e.g., quality, consistency, reliability).
  • Define metrics with Managers to measure team progress, data / solution quality, and the state of engineering / operations.
  • Think strategically and make tradeoffs, as your decisions will impact the organization's infrastructure (including resources and costs).
  • Communicate ideas effectively, both verbally and in writing, to all types of stakeholders. Produce strategic documentation.
  • 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 同僚が実装した新しいMLOpsツールの説明を受ける。前から欲しかったInput Feature Validation機能がついており感動
  • 11 : 00 プロジェクトメンバーと一緒にHyper Parameter Tuning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。Loss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 Hyper Parameter tuneの結果を確認。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DEと一緒に書く
  • 18 : 00 明日のProject Weeklyの準備。各メンバーの進捗をSlackで確認し、事前にアドバイスをいくつか提供。Notebookに作ってくれたFigureを保存
  • 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

    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機械学習・最適化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
  • 2の領域についてはニーズが高まっており、開発を加速しています。一例を挙げると、件数ベースで新たな開発ニーズの80%を占めるとともに、Business Impactも従来のプロジェクトにくらべ非常に大きくなっています。

    1年が経過したばかりですが、非常に期待を集めている成長著しい領域となります。

    Our team provides Data Science solutions, and our main missions are the following three :

  • 1 : Overhaul and maintain a large-scale Data Mart to comprehensively manage and analyze trunk transportation information
  • 2 : Provide machine learning, optimization algorithm solutions utilizing the data from the above 1
  • 3 : Provide Data Pipeline and Dashboard solutions to derive Business Insights using the data from the above 1
  • In particular, there is a growing demand in the area 2, and we are accelerating the development.

    BASIC QUALIFICATIONS

  • Bachelor's degree
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical / mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 4+ years of data scientist experience
  • Practical knowledge of machine learning model and solution development, as well as the ability to implement them (e.g., data preprocessing, base model selection, architecture design, hyperparameter tuning, MLOps).
  • Business Level Japanese or English
  • PREFERRED QUALIFICATIONS

  • Experience as a leader and mentor on a data science team
  • Experience managing data pipelines
  • 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • Experience of Optimization such as genetic algorithm, BEAM search, gradient method, Bayesian
  • Experience of Graph algorithm such as DFS, BFS, Dijkstra, Maximum Flow, Route Planning, Delivery Planning, Dynamic Programming
  • Business Level English
  • Our inclusive culture empowers Amazonians to deliver the best results for our customers.

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    Data Scientist • Tokyo, JPN

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