Sr. Applied Scientist, Selling Partner Communities (SPC)

Amazon; Milano; In loco; EUR 129.000 - 225.000; Tempo pieno

Descrizione del lavoro

A global technology leader seeks a Senior Applied Scientist to enhance seller experiences through innovative AI and machine learning solutions. With responsibilities including data analysis and model development, this role requires a PhD or Master's degree along with significant experience in machine learning. Ideal candidates will demonstrate strong programming skills and a proactive approach to problem-solving in a fast-paced environment.

Competenze

• 3+ years of experience in building machine learning models for business applications.
• Experience with neural deep learning methods and machine learning.
• Strong programming skills in Java, C++, or Python.

Mansioni

• Handle challenging problems impacting millions of selling partners.
• Independently collect and analyze data.
• Design and deliver scalable models using programming and machine learning.

Conoscenze

Machine learning model building

Programming in Java, C++, Python

Neural deep learning methods

Formazione

PhD or Master's degree with 6+ years of experience

Strumenti

R

TensorFlow

Hadoop

Descrizione del lavoro

Sr. Applied Scientist, Selling Partner Communities (SPC)

Job ID: 3132524 | Amazon.com Services LLC

The Selling Partner Communities (SPC) organization is dedicated to ensuring every Selling Partner (SP) achieves satisfaction with their Amazon selling experience. SPC serves as a vital bridge between sellers/vendors and Amazon, creating and managing platforms where they can connect, share knowledge, and receive help. The team's mission encompasses listening to SP feedback, advocating for experience improvements, and empowering SPs through effective, relevant, and timely communications that demonstrate Amazon's commitment to building lasting partnerships.

We are seeking a Sr. Applied Scientist to join our Communities team. The successful candidate is a skilled scientist capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment.

Key Job Responsibilities

• Handle challenging problems that directly impact millions of selling partners


• Independently collect and analyze data


• Design, develop and deliver scalable models, using any necessary programming, machine learning, and statistical analysis software


• Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research


• Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software


• Participate in design and implementation across teams to contribute to initiatives and develop optimal solutions that benefit the SPC organization


• Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.

About the Team

The Selling Partner Communities (SPC) organization serves as a vital bridge between SPs and Amazon, creating and managing platforms where sellers can connect, share knowledge, and receive help. The team's mission encompasses listening to feedback, advocating for experience improvements, and empowering SPs through effective, relevant, and timely communications that demonstrate Amazon's commitment to building lasting partnerships.

Within SPC, the Science team plays a critical role in leveraging artificial intelligence and machine learning technologies to enhance seller experiences and drive data-driven decisions. The team serves as technical advisors helping shape the organization's scientific vision and strategy, identifying and tackling intrinsically hard, previously unsolved problems that require novel scientific approaches. The team focuses on developing comprehensive frameworks for measuring and monitoring seller sentiment, improving content discovery and engagement, enhancing operational efficiency for Community Assistance Managers (CAMs), bringing clarity to complex challenges through scientific expertise, and creating AI-powered tools for content generation and validation.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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 . This position will remain posted until filled. Applicants should apply via our internal or external career site.