Data Scientist, Rapid & Rural Logistics (R2L)

DESCRIPTION

The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes!

We are looking for a Data Scientist to join our team and solve some of the most complex business problems!

Key job responsibilities

• Work with product managers, engineers, other scientists, and leadership to identify and prioritize complex problems.
• Interview stakeholders to gather business requirements and translate business problems into data science or analytical problems
• Design, develop, and evaluate highly innovative statistics and ML models
• Guide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Proactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.

A day in the life

In this role, you will be a technical expert with significant scope and impact. You will work with Product and Supply Chain Managers, Business Intelligence Engineers, System Developers and other Scientists, to develop models that solve a wide range of complex and ambiguous business problems, with the main goal to improve customer experience, improve availability of products and reduce supply chain cost. A successful Data Scientist will have bias for action needed in a startup environment, with great leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.

About the team

The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes!

BASIC QUALIFICATIONS

• Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• 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
• Master's degree in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science or related field, or PhD and 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
• Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
• Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• Experience working in a fast-paced, team environment

• Ability to dive deep into complex technical problems and drive change.
• Excellent problem solving skills with a strong attention to detail.

PREFERRED QUALIFICATIONS

• Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
• Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
• Knowledge of machine learning concepts and their application to reasoning and problem-solving
• Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
• Experience working with or evaluating AI systems
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions
• Experience effectively communicating complex concepts through written and verbal communication

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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 m