Senior Applied Scientist, Amazon Ads

Amazon; Toronto; On-site; CAD 95,000 - 130,000; Full time

Job summary

A leading global e-commerce company is seeking a Machine Learning Expert to lead the Applied Science strategy for their Media Planning Science program in Toronto, Ontario. The role involves guiding machine learning projects, conducting data analysis, and collaborating with engineers to optimize models. Candidates should have 3+ years of experience in machine learning model development and a strong academic background in relevant fields. This position promotes an inclusive culture and values diversity.

Qualifications

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

Responsibilities

• Serve as the technical leader in Machine Learning.
• Lead end-to-end Machine Learning projects.
• Conduct hands-on analysis and modeling of large-scale data.

Skills

Machine learning model development

Data analysis and modeling

Statistical analysis

Collaboration with engineers

Education

PhD or Master's degree in a relevant field

Tools

Java

Python

R

Tensorflow

Job description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

We are looking for an accomplished machine learning expert to lead the Applied Science strategy for our Media Planning Science program. In this role, you will work closely with business leaders, stakeholders, and cross-functional teams to drive program success through ML-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact using advanced data techniques and applied science methodologies.

Key job responsibilities

1. Serve as the technical leader in Machine Learning, guiding efforts within the team and collaborating with other teams.
2. Conduct hands-on analysis and modeling of large-scale data to generate insights that boost traffic monetization and merchandise sales while maintaining a positive shopper experience.
3. Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity.
4. Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production.
5. Run A/B experiments, gather data, and perform statistical analysis to validate your models.
6. Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving.
7. Explore and research innovative machine learning approaches to push the boundaries of what’s possible.

About the team
The Media Planning Science team builds and deploys models that provide insights and recommendations for media planning. Our mission is to assist advertisers in activating plans that align with their goals. Our insights and recommendations leverage heuristic and machine learning models to simplify the complex tasks of forecasting, outcome prediction, budget planning, optimized audience selection and measurements for media planners. We integrate our insights into user interfaces and programmatic integrations via APIs, ensuring reliable data, timely delivery, and optimal advertising outcomes for our advertisers.

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.
• Experience in working with Agentic AI and Gen AI applications

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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.