Senior Applied Scientist, Amazon Ads

Amazon Jobs; Toronto; On-site; CAD 100,000 - 130,000; Full time

Job summary

A leading global tech company in Toronto is seeking a machine learning expert to lead the strategy for their Media Planning Science program. In this role, you will drive ML solutions and collaborate with stakeholders to deliver significant business impact. The ideal candidate has 3+ years in machine learning, a PhD or Master's degree, and experience with programming languages like Python and tools such as TensorFlow.

Qualifications

• 3+ years of building machine learning models for business applications.
• Experience with neural deep learning methods.
• Familiarity with large-scale distributed systems.

Responsibilities

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

Skills

Machine learning models development

Data-driven decision making

Statistical analysis

Programming in Python

Team collaboration

Education

PhD in relevant field

Master’s degree with applied research

Tools

TensorFlow

PyTorch

Hadoop

Spark

Job description

Overview

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 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.

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
• 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

Equal opportunity and accommodations

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 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.