Applied Scientist, Machine Learning Accelerator, Selling Partner Services
Nov 15, 2023
Seattle, WA, USA
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by automatically mitigating risk and providing support solutions?
Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-art algorithms to solve real world problems?
Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes?
If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group.
- Use statistical and machine learning techniques to create the next generation of scalable risk management and support systems.
- Analyze and understand large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends.
- Design, development and evaluation of highly innovative models for risk management.
- Work closely with teams of scientists and software engineers to drive real-time model implementations and new feature creations.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Research and implement novel machine learning and statistical approaches.
Please visit https://www.amazon.science for more information
Key job responsibilities
The scope of an Applied Scientist II in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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 https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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. Applicants should apply via our internal or external career site.