Applied Scientist , Sponsored Products

Amazon; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon Ads' Sponsored Products and Brands team applies generative AI to transform how customers discover products and engage with brands worldwide. We seek an Applied Scientist to advance ML, econometrics, and data-engineering challenges across search experiences.

You will own end-to-end ML projects, design experiments, and partner with PMs and engineers to productionize models that improve ad relevance and shopper experience.

Qualifications

• 3+ years of building models for business applications.
• PhD or Master’s degree with 4+ years in CS/ML.
• Proficient in Java, C++, or Python.
• Experience with algorithms, data structures, numerical optimization.
• Experience with neural deep learning methods.

Responsibilities

• Drive end-to-end ML projects with ambiguity, scale and complexity.
• Analyze large data sets to develop ideas and size opportunities; build ML models and analyze value.
• Design A/B experiments and analyze results to derive understanding.
• Build automated processes for large-scale feature generation, model training, validation and serving.
• Collaborate with other scientists and productionize ML models.

Skills

ML modeling

Java

C++

Python

Neural networks

Distributed computing

Education

PhD

Master's degree

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Hadoop

Spark

Job description

Description
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

Description
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

We are seeking an Applied Scientist to join our Supply Science team. This team is within the Sponsored Products team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant ads on the Amazon search page world-wide thereby enhancing the shopper experience. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference and data engineering.
Key job responsibilities
Search Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions of customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business.
As an Applied Scientist on this team you will:

• Drive end-to-end machine learning projects that have a high degree of ambiguity, scale and complexity
• Perform analysis on very large data sets to develop ideas and size opportunities; build machine learning models and conduct analysis to demonstrate potential business value
• Design A/B experiments, working with engineers to launch online experiments; conduct statistical analysis of the experimental results to derive understanding
• Build efficient and automated processes for large-scale feature generation, machine-learning model training, validation and serving. Work with engineers to productionize ML models.
• Develop new and innovative machine learning approaches, and collaborate with the science community.

A day in the life
The Successful Candidate Will Be a Self-starter Comfortable With Ambiguity, Strong Attention To Detail And An Ability To Work In a Fast-paced Environment. Some Examples Of Day-to-day Activities Include

• Dive deep into the data to understand business opportunities and formulate the science problems
• Implement/create ML models to fit the observed data and predict customer response
• Conduct offline analysis to gauge business impact
• Communicate with PMs and engineers to discuss experiment plans and outcomes
• Work with engineers to conduct A/B tests or productionize your models.
• Collaborate with others scientists on problem solving and knowledge sharing.

About The Team
We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon.

Basic Qualifications

• 3+ years of building models for business application experience
• 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 with neural deep learning methods and machine learning

Preferred Qualifications

• Experience in professional software development
• 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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.

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