Data Scientist

About the job

The WW DSP Analytics team is a centralized analytics organization within Amazon's Last Mile Delivery Service Partner (DSP) program. We build best-in-class solutions that enable data-driven decision making across our global DSP ecosystem. Our team partners with internal stakeholders, DSP owners, and cross-functional teams to deliver insights that drive operational excellence, business growth, and the success of small business owners in Last Mile delivery. Our work directly impacts customer experience, driver and station associate experience, DSP success, and Amazon's sustainable growth. We are seeking a passionate Data Scientist with strong machine learning and analytical skills to join our team. You will work on challenging problems in the delivery planning space, applying data science rigor to generate actionable insights that support DSP performance measurement and continuous improvement. Key job responsibilities: 1. Develop Science Solutions for DSP Performance: Design and implement data science solutions to optimize Delivery Service Partner (DSP) operations, capacity planning, and performance measurement across the global DSP network. 2. Apply Advanced Machine Learning Techniques: Leverage solid research experience in Machine Learning and statistical modeling to identify opportunities for improving DSP analytics, forecasting models, and performance measurement systems. 3. Optimize DSP Program Policies and Sentiment Risks: Analyze sentiment risks and enhance existing algorithms that support DSP program management, including scorecard metrics, capacity reliability models, and performance evaluation frameworks. 4. Analyze Business Requirements with Return on Investment (ROI) calculation: Demonstrate superior logical thinking by quickly approaching large, ambiguous problems, translating high-level DSP program requirements into mathematical models, and applying models to predict the return on investment. 5. Build Production-Scale Analytics: Contribute to the development and deployment of scalable data models, dashboards, and automated reporting systems that enable self-service analytics for DSP stakeholders. 6. Accelerate GenAI footprint: Partner with Data Engineers to expand our GenAI tools and improve developer productivity along with raising the bar on data quality. 7. Conduct Independent Data Analysis: Mine and analyze complex datasets across multiple domains (performance metrics, financial data, operational data) using programming and statistical analysis tools to generate actionable insights. 8. Thrive in a Collaborative Environment: Excel in a fast-paced analytics organization that encourages collaborative and creative problem-solving, measure and communicate analytical risks, constructively critique peer work, and align research focuses with DSP program strategic needs. 9. Partner Cross-Functionally: Work closely with Business Intelligence Engineers, program teams, and DSP stakeholders to define KPIs, validate analytical approaches, and ensure insights drive meaningful business outcomes. Basic Qualifications: - 2+ years of data scientist experience - 3+ years of data querying languages (e.g., SQL), scripting languages (e.g., Python) or statistical/mathematical software (e.g., R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - 1+ years of guiding and coaching a group of researchers experience - 1+ years of working with or evaluating AI systems experience - Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM) Preferred Qualifications: - Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)

Requirements

• Machine Learning
• Data Analytics
• Python
• SQL

Qualifications

• Master’s degree in STEM
• 2+ years of data scientist experience

Preferred Technologies

• Machine Learning
• Data Analytics
• Python
• SQL

About the company

Amazon is a global, technology-driven company that focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence.