Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity.
Do you get excited by aerospace, space exploration, and/or satellites? Do you want to help build solutions at Project Kuiper to transform the space industry? If so, then we would love to talk!
Key job responsibilities
- Work cross-functionally with product, business development, and various technical teams (engineering, science, simulations, etc.) to execute on the long-term vision, strategy, and architecture for the science-based global demand forecast.
- Design and deliver modern, flexible, scalable solutions to integrate data from a variety of sources and systems, increasing forecast accuracy over time.
- Work closely with the capacity planning science team to ensure that demand forecasts feed seamlessly into their systems to deliver continuous optimization of resources.
- Lead short and long terms technical roadmap definition efforts to deliver solutions that meet business needs in pre-launch, early-launch, and mature business phases.
- Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Kuiper.
Export Control Requirement
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.
BASIC QUALIFICATIONS
- 4+ years of data scientist 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.
- Experience with statistical models e.g. multinomial logistic regression.
- Experience developing forecasting methodologies.
PREFERRED QUALIFICATIONS
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
- Experience managing data pipelines.
- Experience working with scientists, economists, software developers, or product managers.
- 3+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience.
- Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
- Hands-on experience in building machine learning or optimization models in a business environment using tools such as AWS SageMaker.
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. For individuals with disabilities who would like to request an accommodation, please visit
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
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