Key job responsibilities
- Develop and implement advanced pricing models and algorithms for cross-border logistics operations
- Analyze large datasets to identify patterns, trends, and opportunities for optimization
- Collaborate with cross-functional teams to translate business requirements into data-driven solutions
- Design and execute experiments to evaluate the impact of pricing strategies
- Communicate complex analytical findings to stakeholders and leadership
- Stay up-to-date with the latest developments in pricing science and logistics domains
A day in the life
As a Senior Data Scientist, you will play a pivotal role in driving pricing science innovations for Amazon's imports business. Your day will involve working closely with teams across the organization to understand business challenges, explore data, and develop cutting-edge solutions. You will leverage your expertise in data analysis, machine learning, and pricing strategies to uncover insights and drive impactful decisions. Additionally, you will have opportunities to present your findings, share your knowledge, and contribute to the overall growth of the pricing science community.
About the team
Amazon Global Mile Science & Analytics drives multiple core and advanced science initiatives for Fulfillment by Amazon (FBA) and Retail. Our approach and technology are disruptive, challenging traditional approaches and changing the way the industry operates. We are passionate about pricing and cross-border logistics spaces, and we foster an environment of continuous learning and innovation.
BASIC QUALIFICATIONS
- 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
- 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 or similar role involving data extraction, analysis, statistical modeling and communication experience
- Experience with statistical models e.g. multinomial logistic regression
PREFERRED QUALIFICATIONS
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
- Prior experience in pricing science, revenue optimization
- If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
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.