招聘
必备技能
Python
SQL
AWS
Swift
Tableau
Machine Learning
As a core member of the AMZL ACES PMO BI & Analytics team, you will contribute to the overall optimization of the last-mile operations network in Japan. Leveraging BI tools and AI technology, you will build an analytical foundation that enables leadership to make swift decisions.
By applying statistical knowledge in practice and pursuing the truth behind data, you will deliver insights from new perspectives beyond traditional KPIs. With a solid understanding of processes and a bias for action, you will analyze and improve process challenges in a data-driven manner, contributing to continuous improvement, operational excellence, and maximization of customer value at Amazon Logistics Japan.
AMZL ACES PMO BI & Analytics teamの中核メンバーとして、日本のラストマイルにおけるオペレーションネットワークの全体最適化に貢献します。BIツールとAI技術を活用し、リーダーが迅速な意思決定を行うための分析基盤を構築します。
統計的知識を実務に応用し、データの背後にある真理を追究することで、従来のKPIにとらわれない新しい視点からの洞察を提供します。プロセスを正しく理解する知識と行動力を持ち、データドリブンでプロセスの課題を分析して改善を行います。Amazon Logistics Japanにおける継続的な改善と卓越したオペレーション、そして顧客利益の最大化に貢献します。
Key job responsibilities
・Design, implement, and operate complex data analysis projects
・Develop dashboards and reports using BI tools such as Quick Sight and Tableau
・Conduct anomaly detection, trend analysis, and predictive analysis using statistical methods
・Automate and streamline analysis leveraging AI/ML tools
・Pursue the truth behind data and provide actionable insights
・Propose data-driven analysis and recommendations for process improvement
・Define and implement analysis requirements in collaboration with stakeholders
・Monitor data quality and propose improvements
・Demonstrate Bias for Action and deliver results
- 複雑なデータ分析プロジェクトの設計・実装・運用
- Quick Sight、Tableau等のBIツールを用いたダッシュボード・レポートの開発
- 統計的手法を用いた異常検知、トレンド分析、予測分析の実施
- AI/MLツールを活用した分析の自動化と効率化
- データの背後にある真理を追究し、アクショナブルなインサイトの提供
- プロセス改善のためのデータドリブンな分析と提案
- ステークホルダーとの協働による分析要件の定義と実装
- データ品質の監視と改善提案
- Bias for Actionを持ち、結果を提供
Basic Qualifications
- Bachelor's degree (Computer Science, Statistics, Mathematics, Engineering, or related field)
- 3+ years of practical experience in Business Intelligence, Data Analytics, or Data Science
- Practical SQL experience and ability to write complex queries
- Experience developing with BI tools (Quick Sight, Tableau, Power BI, etc.)
- Foundational knowledge and practical experience in statistical analysis (mean, variance, correlation analysis, etc.)
- Experience in data analysis using programming languages such as Python or R
- Understanding of data visualization best practices
- Excellent communication skills (Japanese and English)
- Ability to correctly understand processes and analyze challenges in a data-driven manner
Preferred Qualifications
- Master's degree (Statistics, Data Science, or related field)
- Data analytics experience in AWS environments (Redshift, Athena, S3, etc.)
- Foundational knowledge and practical experience with machine learning and AI tools
- Experience designing and implementing ETL processes
- Analytics experience in logistics, supply chain, or last-mile delivery domains
- Practical experience in statistical hypothesis testing and A/B testing
- Experience in data modeling
- Lean Six Sigma Yellow Belt certification or above
- Entrepreneurial mindset with experience proactively tackling problem-solving
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
2.9
10条评价
工作生活平衡
2.8
薪酬
3.7
企业文化
2.5
职业发展
2.3
管理层
2.1
35%
推荐给朋友
优点
Good pay and compensation
Strong benefits package
Flexible scheduling options
缺点
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
薪资范围
4个数据点
L2
L3
L4
L5
L6
L2 · Business Development L2
0份报告
$164,290
年薪总额
基本工资
$65,716
股票
$82,145
奖金
$16,429
$115,003
$213,577
面试经验
10次面试
难度
3.7
/ 5
时长
21-35周
录用率
20%
体验
正面 10%
中性 10%
负面 80%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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