Amazon
Senior Applied Scientist, Selling Partner Promotions
Amazon, Seattle, Washington, us, 98127
Senior Applied Scientist, Selling Partner Promotions
Are you interested in applying your background in machine learning, data science, and statistical analysis to massive real-world data and impact the lives of hundreds of millions of Amazon customers? Do you like to own end-to-end business problems and metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit for our Promotion Science Team at Amazon.
At Promotion Science, our vision is simple - we want to run the best promotions in the industry. Through technology, we seek to constantly increase the quality of promotions to delight customers and provide ROI for Selling Partners. In this role, you will build scalable, accurate, and interpretable statistical and machine learning models to forecast and rank promotions as well as measure their incremental business values.
Key job responsibilitiesAs a Senior Applied Scientist on this team, you will:
- Tackle ambiguous and complex science problems in time-series analysis, causal inference, statistical modeling, recommendation, and reinforcement learning.- Build statistical and machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.- Run A/B experiments, gather data, and perform statistical tests.- Interpret and present scientific results to business stakeholders and leadership and drive decision making.- Guide and mentor other scientists on the team.
- 5+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 4+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
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.
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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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Are you interested in applying your background in machine learning, data science, and statistical analysis to massive real-world data and impact the lives of hundreds of millions of Amazon customers? Do you like to own end-to-end business problems and metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit for our Promotion Science Team at Amazon.
At Promotion Science, our vision is simple - we want to run the best promotions in the industry. Through technology, we seek to constantly increase the quality of promotions to delight customers and provide ROI for Selling Partners. In this role, you will build scalable, accurate, and interpretable statistical and machine learning models to forecast and rank promotions as well as measure their incremental business values.
Key job responsibilitiesAs a Senior Applied Scientist on this team, you will:
- Tackle ambiguous and complex science problems in time-series analysis, causal inference, statistical modeling, recommendation, and reinforcement learning.- Build statistical and machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.- Run A/B experiments, gather data, and perform statistical tests.- Interpret and present scientific results to business stakeholders and leadership and drive decision making.- Guide and mentor other scientists on the team.
- 5+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 4+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
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.
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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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