Amazon Advertising is one of Amazon's fastest growing and most profitable
businesses. Amazon's advertising portfolio helps merchants, retail vendors, and
brand owners succeed via native advertising, which grows incremental sales of
their products sold through Amazon. The primary goals are to help shoppers
discover new products they love, be the most efficient way for advertisers to
meet their business objectives, and build a sustainable business that
continuously innovates on behalf of customers. 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!
The ADSP Forecasting team's vision is to build the best in class forecasting
products offered by any DSP to allow advertisers to forecast campaign outcomes
across the full market funnel. Our goal is to empower advertisers using Amazon
demand side platform to make informed decisions by providing predictions and
recommendations of supply and ad-performance. Our forecasting models and
analytical solutions will also help internal teams (sales, PSC, supply desk etc)
to gain insights into forecasted supply, demand and ad performance to make the
best business decisions. The team comprises scientists and engineers who own
end-to-end projects - data collection, analysis, ideation, and prototyping, to
development, metrics and monitoring. The models and services are integrated
directly with Amazon's Ads eco system and the forecasts are used to drive key
business decisions at the VP/SVP level. We are a team of Applied Scientists and
Engineers, who are passionate about solving technical problems in the Ad
Forecasting space with models using Machine Learning, Bayesian Statistics, etc.
You will join a group of highly talented PhDs with diverse background to design,
prototype, and implement models to deliver impact directly to customers. You
will have the opportunity to present your work in science communities and to
leadership
As a Applied Scientist on this team, you will:
- Be the technical leader in Machine Learning; lead efforts within this team and
across other teams.
- Perform hands-on analysis and modeling of enormous data sets to develop
insights that increase traffic monetization and merchandise sales, without
compromising the shopper experience.
- Drive end-to-end Machine Learning projects that have a high degree of
ambiguity, scale, complexity.
- Build machine learning models, perform proof-of-concept, experiment, optimize,
and deploy your models into production; work closely with software engineers to
assist in productionizing your ML models.
- Run A/B experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data
analysis, machine-learning model development, model validation and serving.
- Research new and innovative machine learning approaches.
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 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.
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
[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.
