Sr. Applied Scientist, Sales AI

Qualifications

• 5+ 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

Responsibilities

• This role combines scientific leadership, organizational ability, technical strength, product focus, and business understanding
• You will conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business
• Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions
• Guide the technical approach for the design and implementation of successful models and algorithms
• Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities
• Run regular A/B experiments, gather data, and perform statistical analysis
• Work closely with software engineers to deliver end-to-end solutions into production
• Improve the scalability, efficiency, and automation of large-scale data analytics, model training, deployment, and serving

Full Description

Job Description:

Transforming Advertising and B2B Sales

We are a growing science and engineering team with an exciting charter, seeking passion, innovative thinking, and creativity to take our products to new heights.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, defining and delivering a collection of advertising products that drive discovery and sales.We break fresh ground in product and technical innovations every day.

Within the Advertising Sales organization, we are building a central AI/ML team, seeking top science talent to build new, science-backed services to drive success for our customers.

Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency.

About the Role

This role combines scientific leadership, organizational ability, technical strength, product focus, and business understanding.

You will conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business.

Key Responsibilities:

• Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions.

• Guide the technical approach for the design and implementation of successful models and algorithms.

• Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities.

• Run regular A/B experiments, gather data, and perform statistical analysis.

• Work closely with software engineers to deliver end-to-end solutions into production.

• Improve the scalability, efficiency, and automation of large-scale data analytics, model training, deployment, and serving.

About Us

Sales AI is a central science and engineering organization within Amazon Advertising Sales, powering selling motions and account team workflows via state-of-the-art AI/ML services.

We are investing in a range of sales intelligence models, including the development of advertiser insights, recommendations, and Generative AI-powered applications throughout account team workflows.

Requirements

BASIC QUALIFICATIONS:

• 5+ 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.