Our team is uniquely positioned to help solve some of the biggest challenges on behalf of our selling partners. We consume vast amounts of text data that with the right models can unlock deep insight into what our selling partners care about most. We use Machine Learning (ML) in production to personalize their experience of our products to ensure they can quickly find the best quality content both from their seller community and content that we generate. We can build generative models that guide our Community Advisors in ensuring they are making the most impact for our selling partners; by proactively building community instead of reactively solving issues. We use accurate and appropriate scientific techniques, built to scale, that directly impact the experience and perception of our selling partners globally.
We are seeking an Applied Scientist to join the SPCS Data Science & Analytics (DSA) team. The Data Science and Analytics (DSA) team within the Selling Partner Empowerment, Communities and Trust (SPECT) organization empowers data-driven workflows to apply data at scale. Our engineers and analysts transform business needs into secure solutions which enables customers and systems to efficiently access the data they need. Our scientists extract deep insights from data to influence strategic product decisions and directly integrate ML models into selling partner systems. Together, we design and deploy reusable components to apply these insights consistently and expediently to improve the ways customers and selling partners experience Amazon’s offerings.
Key job responsibilities
– Use machine learning and analytical techniques to create scalable solutions for solving seller problems.
– Analyze and extract relevant information from large amounts of historical multimodal data to help automate and optimize key processes.
– Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation in production.
– Research and implement novel machine learning and statistical approaches.
– Apply modeling techniques to large amounts of text data for personalization and generating content.
– Work closely with data & software engineering teams, and business stakeholders, to build model implementations and integrate successful models and algorithms in production systems at very large scale.
About the team
The Selling Partner Communities and Satisfaction (SPCS) organization builds lasting connections with and among our selling partners. We help drive their success, working together to ensure that Amazon’s stores are a great place for our selling partners to build and maintain thriving businesses. Our vision is to be the most Seller-centric online global community, creating destinations for knowledge, news, inspiration, and celebration. We are dedicated to helping selling partners develop their full potential and achieve success in our Amazon store.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | San Diego, CA, USA | Seattle, WA, USA | Sumner, WA, USA | Tempe, AZ, USA
BASIC QUALIFICATIONS
– 3+ years of building machine learning models or developing algorithms for business application experience
– PhD, or Master’s degree and 3+ years of CS, CE, ML or related field experience
– Experience programming in Java, C++, Python or related language
– Depth in more than one and breadth across several domains in ML, such as Deep Learning, Natural Language Processing, Computer Vision, and/or Causal Modeling, as well as a strong foundation in ML fundamentals
PREFERRED QUALIFICATIONS
– A PhD in Machine Learning, CS, Mathematics, Statistics or another highly quantitative field
– Experience with LLMs or other NLP techniques
– Ability to produce code to implement models at scale in a production environment
– Experience working with engineering teams to design and build large-scale ML systems
– Experience with AWS applications and services, including using infrastructure as code (IaC) e.g. CloudFormation, CDK.
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.