- 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 a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
- Experience working with data engineers and business intelligence engineers collaboratively
- Experience working with scientists, economists, software developers, or product managers
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Who are we?
Do you want to build Amazon's next $100B business? We're not just joining the shipping industry—we're transforming how billions of packages move across the world every year. Through evolving Amazon's controlled, predictable fulfillment network into a dynamic, adaptive shipping powerhouse we are building an intelligent system that optimizes in real-time to deliver on the promises businesses make to their customers.
Our mission goes beyond moving boxes—we're spinning a flywheel where every new package makes our network stronger, faster, and more efficient. As we increase density and scale, we're revolutionizing shipping for businesses while simultaneously strengthening Amazon's own delivery capabilities, driving down costs and increasing speed for our entire ecosystem.
What will you do?
Amazon shipping is seeking a Senior Data Scientist with strong statistical, ML and forecasting skills to work in an embedded team, partnering closely with commercial, product and tech. This person will primary be responsible for developing cutting marginal cost prediction models for Amazon shipping’s spot channel. As a Senior Data Scientist, you will be part of a science team responsible for improving price discovery across Amazon shipping, measuring the impact of model implementation, and defining a roadmap for improvements and expansion of the models into new unique use cases. This person will be collaborating closely with business and software teams to research, innovate, and solve high impact costing problems facing the worldwide Amazon shipping business.
Key job responsibilities
* Design and develop robust forecasting models for shipping costs, customer demand, and transportation capacity.
* Partner with other scientists to dynamically predict prices to maximize capacity utilization.
* Build and implement robust ML models for customer segmentation, profitability maximization, performance outlier identification, and risk prediction
* Use forecasting, statistical, machine learning and analytical techniques to create scalable solutions for business problems.
* Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders.
* Educate non-technical business leaders on complex modeling concepts, and explain modeling results, implications, and performance in an accessible manner.
* Independently identify and pursue new opportunities to leverage science insights.
* Opportunity to expand into other domains such as causal analytics, optimization and simulation.
About the team
Amazon Shipping's pricing team empowers our global business to find strategic harmony between growth and profit tradeoffs, while seeking long term customer value and financial viability. Our people and systems help identify and drive synergy between demand, operational, and economic planning. The breadth of our problems range from CEO-level strategic support to in-depth mathematical experimentation and optimization. Excited by the intersection of data and large scale strategic decision-making? This is the team for you!
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