Amazon
Applied Scientist, Advertiser Success
Amazon, Seattle, Washington, us, 98127
Job ID: 2809625 | Amazon.com Services LLCWe are seeking an entrepreneurial, innovative and self-driven Senior Applied Scientist to join our team, and help build a brand new Advertising product together. Your mission will be to leverage science and technology to help hundreds of thousands of independent sellers grow their business on WW Amazon marketplaces attracting new customers while also building customer loyalty.You will use ML modeling to build predictive modeling solutions to help brand owners connect with potential shoppers on Amazon websites and video channels (IMDB, FireTV, Twitch, Amazon.com etc). You can change the life of local business owners while taking ownership to solve technical challenges from delivering millions of global advertising campaigns and generating brand insights and recommendations for all our advertisers with superfast response time.The Sponsored Brands Advertiser Control team is a versatile environment, with a wide variety of challenges. We guide advertisers to make informed decisions by recommendations, sharing insights, and forecasts. We help advertisers deliver effective campaigns automatically by optimizing campaign settings on behalf of them. We enable advertisers to achieve brand advertising goals with maximum efficiency. We have the opportunity to deliver social impact, own technical problems, thought diversity, and business impact.As an Applied Scientist on this team, you will:
Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.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.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.Recruit Applied Scientists to the team and provide mentorship.BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experiencePhD, or Master's degree and 6+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED 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 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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.Posted:
October 28, 2024 (Updated about 6 hours ago)
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Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.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.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.Recruit Applied Scientists to the team and provide mentorship.BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experiencePhD, or Master's degree and 6+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED 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 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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.Posted:
October 28, 2024 (Updated about 6 hours ago)
#J-18808-Ljbffr