Kuiper's Commercial Revenue Operations (CRO) team is looking for a Senior Data Scientist to work hands on from concept to delivery on statistical analysis, prescriptive and predictive analysis, and machine learning implementation projects. We are looking for a problem solver with strong analytical skills and a solid understanding of statistics & Machine learning algorithm as well as a practical understanding of collecting, assembling, cleaning and setting up disparate data from enterprise systems to build models to help solve complex problems in the areas of sales forecasting, customer segmentation, what if simulations and demand forecasting.
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
Key job responsibilities
• Develop ML models to measure long term impact of seller behaviors
• Collaborate with product and engineering teams both within and outside of the CRO team to launch models and develop insights.
• Use optimization, statistical, machine learning and analytical techniques to create scalable solutions for business problems.
• Design, development and evaluation of highly innovative models for forecast, optimization and experimentation.
• Research, experiment and implement novel approaches.
• Work closely with other scientists in the team and across teams.
• Work and collaborate effectively with product managers and software engineering teams to build algorithms and models and integrate successful models and algorithms in production systems.
• Use the best practices in science: data integrity, design, test, and implementation and documentation.
• Mentor and guide junior members in the team.
• Contribute to Amazon's Intellectual Property through patents and internal and external publications
About the team
Kuiper Commercial Revenue Operations (CRO) is responsible for the business strategy, operations and systems for Kuiper's commercial business across multiple industry segments in multiple countries.
BASIC QUALIFICATIONS
- 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 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
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.