Toronto, Ontario

DESCRIPTIONAmazon's Sponsored Products advertising business is one of the fastest growing areas in the company. Have you ever wondered what happens behind that “Sponsored” label you see on Amazon? The Sponsored Products Marketplace team creates and optimizes the systems that match advertiser demand (ads) with page supply (placements) using a combination of data-driven product innovation, machine learning, big data analytics, and low latency/high-volume engineering. By the time organic search results are ready, we've processed all of the candidate ads and determined which ones are delivered to the page. We do that billions of times per day, resulting in millions of engagements with products that otherwise might not have been seen by shoppers. The business and technical challenges are significant. Fortunately, we have a broad mandate to experiment and innovate, and a seemingly endless range of new opportunities to build a big, sustainable business that helps Amazon continuously delight all of our customers.We're looking for an innovative and customer-obsessed Sr. Applied Scientist who can help us take our products to the next level of quality and performance by creating state-of-the-art models to improve our ability to predict entity relationships, forecast the impact of advertiser actions, and optimize ad selection for different contexts. We embrace leaders with a startup mentality -- those who have a disruptive yet clear mission and purpose, an unambiguous owner's mindset, and a relentless obsession for delivering amazing products.As Sr. Applied Scientist on the Product Targeting team, you will work alongside business leaders, other scientists, and software engineers to deliver recommenders and forecasters based on ML, DL, and RL from idea to production. You will be responsible for bridging the experimental domain with the production domain by building robust and efficient computational pipelines to scale up models, keeping the models fresh, and ensuring that real-world corner cases are handled correctly. You'll own significant products and features from inception through launch, and will work with Product Managers, other Scientists, and Engineers to make your efforts wildly successful. You will lead the science program for our team, providing input to strategic decision making on topics such as program direction/vision, roadmap, and staffing. If this sounds like your sort of challenge, read on.Characteristics indicative of success in this role:· Highly analytical: You solve problems in ways that can be backed up with verifiable data. You focus on driving processes, tools, and statistical methods which support rational decision-making.· Technically fearless: You aren't satisfied by performing 'as expected' and push the limits past conventional boundaries. Your dial goes to '11'.· Engaged by ambiguity: You're able to explore new problem spaces with unique constraints and non-obvious solutions.· Team obsessed individual contributor: You help grow your team members to achieve outstanding results. You've learned that big plans generally involve collaboration and great communications.· Quality obsessed: You recognize that professional scientists build high quality model development and evaluation frameworks to ensure that their models can provably meet launch criteria, or efficiently iterate in the framework until they do.· Humbitious: You’re ambitious, yet humble. You recognize that there’s always opportunity for improvement. You use introspection and feedback from teammates and peers to raise the bar.Primary Responsibilities:· Apply machine learning and analytical techniques to create scalable solutions for business problems· Work closely with software engineering and product teams across the organization to drive model implementations and new feature creations· Work closely with business stakeholders to identify opportunities for current model improvements and new models to significantly benefit the business bottom-line· Collaborate with scientists within the Ads organization as well as other parts of Amazon to share learnings move the state-of-the-art forward· Establish scalable, efficient, automated processes for data analyses, model development, model validation and model implementation· Research and implement novel machine learning and statistical approachImpact and Career GrowthYou will invent new shopper and advertiser experiences, and accelerate the pace of Machine Learning and Optimization.Influence customer facing shopping experiences to helping suppliers grow their retail business and the auction dynamics that leverage native advertising, this role will be powering the engine of one the fastest growing businesses at Amazon.Define a long-term science vision for our ad marketplace, driven fundamentally from the needs of our customers, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams.This is a role that combines science leadership, organizational ability, technical strength, product focus and business understanding.Why you love this opportunityAmazon is investing heavily in building a world class advertising business and 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 are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.Team video ~ https://youtu.be/zD_6Lzw8raEBASIC QUALIFICATIONS· 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 languagePREFERRED QUALIFICATIONS· Strong publication record with novel research contributions· Proven success in applying ML/DL/RL models to practical problems· Experience with with any of: NLP, transfer learning, BERT, pair modeling, topic modeling, similarity, relevance.· Expertise in working with big-data in map/reduce setting using Spark, EMR, Pig, etc.· Experience with AWS and data-oriented tools such as Sagemaker, Airflow, ElasticSearch, Airflow, etc.· Experience in online advertising domain (particularly, ad targeting and serving) is a big 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/ontario#sspajobs #spmpjobs #sptargjobs