Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. The Global Advertising Partner Development team within Advertising helps suppliers, agencies, marketers, authors, content creators, designers, non-endemic advertisers and developers to scale their use of Amazon Advertising and grow their business by surfacing a diverse selection of products to millions of worldwide Amazon customers. We do this via software tools and marketing/engagement programs that enable developers (internal and external) and partners (agencies and tool providers) to better serve advertiser needs.
We are looking for a senior applied scientist capable of using statistical and machine learning techniques to create state-of-the-art solutions for non-trivial, and arguably, unsolved problems. If you are results driven, interested in how to apply advanced machine learning and causal analysis techniques, love to work with advertising, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact our customers, we want to talk to you.
Key responsibilities include:
· Partnering with economists, scientists, developers, and senior team members to drive a new science agenda for causal analysis and ML in advertising.
· Driving applied science projects end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring.
· Providing technical leadership, researching new approaches to drive continued scientific innovation.
· Presenting results, reports, and data insights to both technical and business leadership.
· Build machine learning models and utilize data analysis to deliver scalable solutions to business problems.
· 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.
· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production
· Research new machine learning approaches.
Why you love this opportunity
Amazon is investing heavily in building a world-class advertising business. We are responsible for defining and delivering a collection of self-service performance 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 break fresh ground to create world-class products. We are 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 shopper and advertiser 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 fundamentally 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
· PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
· 3+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· Proven success in applying Machine Learning models to real-world business problems
· Familiar with Machine Learning tools, but an expert in understanding the underlying algorithms.
· Experience working with Causal Inference.
· Experience working with AWS technologies such include S3, Sagemaker, EMR, EC2, Redshift, etc.
· Experience working with big-data in map/reduce setting through, e.g., Spark, EMR and scaling models.
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