Applied Scientist, Forecasting Science

Key Skills

C++, Java Programming, Large scale data processing, Machine learning techniques, Python Programming, SQL

Job Description

Job summary

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.

This opportunity is for the Advertising Forecasting Science team, which consists of scientists and engineers based in Palo Alto, California and New York City. The team builds forecasting models for advertising campaigns and financial planning, with revenue exceeding tens of billions of dollars. In addition, the forecasting science team makes auction prediction and handles bid optimization for billions of requests per day, impacting the company’s performance directly using advanced Machine Learning algorithms.

As an Applied Scientist on this team, you will:

• Drive applied science (machine learning) projects end-to-end - from ideation, analysis, prototyping, development, metrics, and monitoring.
• Conduct deep analyses on massive Ad user and contextual data sets
• Propose viable modelling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results.
• Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions.
• Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting.
• Stay familiar with the field and apply state-of-the-art Machine Learning techniques to our domain problems, around forecasting, bidding, allocation, and optimization.
• Produce peer-reviewed scientific paper in top journals and conferences.
• Present results, reports, and data insights to both technical and business leadership.
• Work across teams and lead a group of talented scientists and engineers to solve problems in the domains of forecasting, auction theory, bid optimization, and user clustering.

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.

BASIC QUALIFICATIONS

• Master's in Computer Science, Mathematics, Machine Learning, or related quantitative field
• Experience programming in Java, C++, Python or related language

PREFERRED QUALIFICATIONS

• Published research work in academic conferences or industry circles.
• Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
• Technical leadership in machine learning.
• Effective verbal and written communication skills with non-technical and technical audiences.
• Experience working with real-world data sets and building scalable models from big data.
• Thinks strategically, but stays on top of tactical execution.
• Exhibits excellent business judgment; balances business, product, and technology very well.
• Experience in computational advertising.