What are the responsibilities and job description for the Senior Applied Scientist, Featured Merchant Algorithm position at Amazon?
Description
Do you ever struggle to explain your work? How's this: "Do you shop at Amazon? Do you know that box that says 'Add to Cart' and shows a price? Our team owns the model which picks that offer and the customer experience around the display of the offer price and the elements surrounding the 'Add to Cart' button which inform a purchase decision. We pick and display offers several billion times a day across all surfaces (mobile app, mobile web, desktop, Alexa
shopping) worldwide.
Our mission is to be the world’s first and most
trusted choice for every customer on earth to discover and evaluate any product or service.
Our team blends machine learning models to rank and select the best offer from the most trusted merchant for all products sold on Amazon along with a world-class front-end user experience for offer comparison to our global customers. We are responsible for the experiences and services that enable developers, including our own, to create
tailored shopping experiences for every customer, product, business and marketplace offered by Amazon. We build scalable and extensible frameworks which allow for many teams at Amazon to innovate within the Offers Experience
in a federated manner.
If you are passionate about influencing and delivering the next-generation Amazon customer buying experience, we want to meet you.
We are looking for a Senior Applied Scientist to join one of the most impactful and visible teams in Amazon. In this role you will work with business stakeholders throughout Amazon and provide technical direction and business expertise to strategize and help launch new businesses and features for our customers. You will use data to justify customer friendly decisions and present customer and financial impact of the changes we make to our stakeholders. You will work closely with other scientists, engineers, product managers, TPMs, managers, and senior leadership team to understand and drive business impact. Successful candidates will have experience working on multiple projects with different stakeholders, make data driven decisions, have strong communication skills to interact with executives, non-technical and technical individuals and have a high technical bar along with a passion
for people and project management. This is an opportunity to work with a team that drives one of the most coveted real estate in the E-commerce, the Amazon ‘Buy Box’ on Amazon Product Detail Page, Amazon Search Page , multiple buying widgets etc. on the Amazon desktop, mobile and tablet environments.
Key job responsibilities
* Build, innovate and maintain FMA's key offer selection algorithms
* Collaborate with peer scientists and partner organizations to align on strategic algorithmic inputs
* Research and deliver innovative techniques for ranking, simulation and evaluation systems
* Build and maintain AI, ML and LLM integrations
Basic Qualifications
- 3 years of building machine learning models for business application experience
- PhD, or Master's degree and 6 years of applied research experience
- Experience programming in Java, C , Python or related language
- Experience with neural deep learning methods and machine learning
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.