AmazonData Scientist , Leo Customer Terminal
Amazon is hiring a Data Scientist , Leo Customer Terminal. It pays $136k-$184k a year and Level rates it ; you can apply on Level.
AI in this role
Develop advanced analytics, predictive models, and LLM fine-tuning datasets for satellite user terminals.
As a Data Scientist, you will be responsible for developing advanced analytics and machine learning solutions for user terminals. You will develop predictive models to proactively identify possible user terminal failures in the field. You will work in a collaborative environment with a multi-disciplinary team, including constellation, RF, antenna, silicon, algorithm, and software engineers.
Key job responsibilities
As a Data Scientist, you will develop analytic tools for a team developing current and future user terminals. Your responsibilities include:
• Develop statistical and analytical tool to enable the regression decision from on-orbit and lab measurement of user terminals
• Publish documents and create compelling visualizations and presentations to communicate insights to stakeholders
• Create and manage datasets for continued pre-training and supervised fine-tuning of LLMs
• Develop scalable visualizations for analysis of user terminal performance
• Work closely with constellation, RF, antenna, silicon, algorithm, and software engineers to root-cause the failures using data as the primary tool
• Drive consensus on metrics and analysis approaches to support product development strategy
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.
A day in the life
As a Data Scientist in the LEO Customer Terminal Team, you will work daily with satellite constellation, algorithm, RF, antenna, silicon, hardware, and software teams in a collaborative environment. Your focus will be using data as an intelligence source to enable design decisions for the team.
About the team
The LEO Customer Terminal team is responsible for developing both outdoor and indoor devices that enable customers to access internet service via the LEO satellite network. We own the entire process from early prototypes through mass production, including requirements documentation, architecture definition, hardware development, algorithm development, and all integration and verification testing.
Basic qualifications
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Bachelor’s degree in electrical engineering, physics, mathematics, or an equivalent field
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of experience with machine learning/statistical modeling, data analysis tools and techniques, and understanding of parameters that affect their performance
- Experience conducting and documenting trade studies and design trades
Preferred qualifications
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
- Strong analytical, problem-solving, and communication skills
- Ability to work in a small team and drive beyond expectations to deliver results
- Master's or PhD degree in electrical engineering, physics, mathematics, or an equivalent field
- Experience in a ML or data scientist role with a large technology company
- Experience taking a leading role in building complex models
- Experience in satellite constellation design and management trades
- Experience modeling orbits, reference frames, and efficiently using vector geometry to simulate time-varying relative geometry of satellites and ground nodes
- Experience working with mobility satellite terminals, such as maritime and aeronautical
- Familiarity with phased array designs and implementations
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 more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Redmond - 136,000.00 - 184,000.00 USD annually
How we rate this
Data Scientist , Leo Customer Terminal at Amazon rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where predictive modeling was part of your work. What did you do?
- Tell me about a project where statistical analysis was part of your work. What did you do?
- Tell me about a project where data visualization was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, Machine learning, Predictive Modeling, Statistical Analysis, and Data Visualization. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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