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 businesses driving 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 Machine Learning Optimization (MLO) team develops algorithms and systems that improve the performance and delivery of Amazon’s Display Advertising campaigns and automates campaign management using machine learning techniques. The team develops and deploys machine learning solutions that drive ad selection, bidding, user response prediction, and automated campaign management. Customers are advertisers and publishers who do business with Amazon.We own the system for batch training of user response prediction models, while the ad serving engineering team owns the real-time model scoring component. This teams owns the system for automated management of advertising campaigns, which can dynamically adjust parameters such as budget, bid prices, and targeting to optimize for campaign performance.
As a Data Scientist on this team, you will:
· Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.
· Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
· Apply statistical and machine learning knowledge to specific business problems and data.
· Build decision-making models and propose solution for the business problem you define.
· - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
· Analyze historical data to identify trends and support optimal decision making.
· Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.
· Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
· Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.
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
· Bachelor's Degree
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 2 years working as a Data Scientist
· Experience in as many of the following areas: causal inferencing, multi-variate testing & design, A/B testing & design, descriptive analytics, and regression analysis.
· Good understanding of supervised and unsupervised learning models.
· Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field
· Expert level knowledge in statistics; sophisticated user of statistical tools.
· Experience processing, filtering, and presenting large quantities (hundreds of millions/billions of rows) of data
· Experience in data applications using large scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
· Broad knowledge of ML methods, statistical analysis, and problem-solving skills.
· Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our customer’s organization.
· Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
· Excellent verbal and written communication skills with the ability to advocate technical solutions for science, engineering, and business audiences.
· Ability to develop experimental and analytical plans for data modeling, use effective baselines, and accurately determine cause-and-effect relations.
· Experience in computational advertising is a plus.
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