Job Location: Remote
Ph.D. degree in economics, labor economics, behavioral economics or related social science field with expertise in econometrics or applied statistics.
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 are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products.
The Partner Science team in GAPD tackles some of our hardest causal inference questions for Amazon Ads, feeding results back to our stakeholders to continue to drive innovation in our partner management initiatives to better serve our customers. The Amazon Advertising Partner Network is a self-service hub for partners (agencies and tool providers) to register their businesses, gain partner accreditation, and access tiered benefits which include educational and marketing resources, badges, performance metrics, developer information, developer metrics and the Advertising API Sandbox (for tool providers). AAPN also helps advertisers (brands, suppliers and vendors) connect with accredited partners via the “Find a Partner” directory. This team resides within the Global Advertising Partner Development team (GAPD) helps suppliers, agencies, marketers, authors, content creators, designers, non-endemic advertisers and developers scale their use of Amazon Advertising worldwide by: 1) fostering innovation from internal and external developers via our software tools and API infrastructure, 2) building retail and advertising tools for advanced advertisers and 3P partners (i.e., agencies and tool providers), 3) providing holistic partner development and technical support across Advertising, and 4) running scaled marketing and education programs to support each of these initiatives.
As a Senior Economist on this team, you will:
- Lead the development of a consistent, integrated framework for assessing casual relationships the multitude of product features and processes.
- Interact with senior leaders (technial and non-techncial) to understand primary use cases for causal inference.
- Independently write technical and business documents to communicate ideas and proposals to various audiences.
- Incorporate new data sources and creative methodology innovations to improve model performance.
- Leverage ML models to build economic models that help customers leverage Amazon’s Advertising solutions most effectively.
- Colloborate with Economists, Applied Scientists, Data Scientists to guide roadmaps.
- Design and analyze experiments (A/B testing etc.) to evaluate different strategies.
- Use large datasets or experiments to make causal inferences or predictions.
- Work with engineers to automate science analysis processes and build scalable measurement solutions.
- Review and audit modeling processes and results for other scientists, both junior and senior.
- Communicate with org leaders and business/engineering teams for models, experiments and data analysis.
- Mentor junior teammates to improve their understanding and application of science to causal economic problems.
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.
Team video https://youtu.be/zD_6Lzw8raE
- Verbal and written communication skills with the ability to advocate technical solutions for science, engineering, and business audiences.
- Experience supporting multiple stakeholders. * Proven track record of solving real business problems.
- Fluency in data analysis languages (e.g., R, Python, SAS, SQL, etc.)
- Experience processing, filtering, and presenting large quantities (hundreds of millions/billions of rows) of data – Experience in 1 or more of the following areas: causal learning, multi-variate testing, hypothesis testing, and A/B Testing
- Knowledge or experience in constructing, estimating, and defending causal statistical models.
- Experience in Python, Stata, R and/or Scala.
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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.
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