Applied Science Manager, Advertising

PhD degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
- Experience programming in Java, C++, Python or related language.
- 3+ years of experience directly managing scientists and/or machine learning engineers.

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

**As an Applied Science Manager in Machine Learning, you will**:

- Directly manage and lead a cross-functional team of Applied Scientists, Data Scientists, Economists, and Business Intelligence Engineers.
- Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments.
- Lead marketplace design and development based on economic theory and data analysis.
- Provide technical and scientific guidance to team members.
- Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment
- Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.
- Develop science and engineering roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects.
- Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
- Collaborate with business and software teams across Amazon Ads.
- Stay up to date with recent scientific publications relevant to the team.
- Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization.

**Why you will love this opportunity**: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

**Impact and Career Growth**: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.

Toronto, ON, CAN
- Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
- Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
- Experience with Big Data technologies such as AWS, Hadoop, Spark, Hive, Lucene/SOLR, or Kafka
- Published research work in academic conferences or industry circles.
- Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization.
- Experience in computational advertising.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.