Principal Applied Scientist, Seller Growth and Insights
Seattle, Washington
Join us in the evolution of Amazon's Seller business! The Selling Partner Recruitment and Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential by using our scaled, automated, and self-service tools.
We aim to accelerate the growth of Sellers by providing tools and insights that enable them to make better and faster decisions at each step of selection management. To accomplish this, we offer intelligent insights that are both detailed and actionable, allowing Sellers to introduce new products and engage with customers effectively. We leverage extensive structured and unstructured data to generate science-based insights about their business. Furthermore, we provide personalized recommendations tailored to individual Sellers' business objectives in a user-friendly format. These insights and recommendations are integrated into our products, including Amazon Brand Analytics (ABA), Product Opportunity Explorer (OX), and Manage Your Growth (MYG).
We are looking for a talented and passionate Principal Scientist to lead our research endeavors and develop world-class statistical and machine learning models. The successful candidate will work closely with Product Managers (PM), User Experience (UX) designers, engineering teams, and Seller Growth Consulting teams to provide actionable insights that drive improvements in Seller businesses.
Key job responsibilities
As a Principal Applied Scientist, you bring business and industry context to science and technology decisions.
You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms.
Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility.
You tackle intrinsically hard problems, acquiring expertise as needed.
You decompose complex problems into straightforward solutions.
We are open to hiring candidates to work out of one of the following locations:
New York, NY, USA | Seattle, WA, USA
BASIC QUALIFICATIONS
• Ph.D. in Computer Science, Mathematics, Statistics, related field, or equivalent experience.
• 10+ years of experience in applied science and software development at large scale.
• Experience building complex software systems that have been successfully delivered to customers.
• Extensive experience building predictive and optimization models.
• Expert knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, informational retrieval.
• Proven track record of leading and mentoring applied scientists.
• Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis.
• Proficiency in, at least, one modern programming language such as C, C++, Java, or Python.
• Ability to take a complex problem from scoping requirements through actual launch of the project.
• Excellent written and oral communication skills.
PREFERRED QUALIFICATIONS
• Experience in website optimization, recommender systems.
• Experience with distributed machine learning systems with billions of data points.
• 10+ years of hands-on experience in predictive modeling and analysis.
• Significant peer reviewed scientific contributions in premier journals and conferences.
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
• Significant peer reviewed scientific contributions in premier journals and conferences.
• Proven track record leading, mentoring, and growing teams of scientists
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 $159,100/year in our lowest geographic market up to $309,400/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. Applicants should apply via our internal or external career site.
We aim to accelerate the growth of Sellers by providing tools and insights that enable them to make better and faster decisions at each step of selection management. To accomplish this, we offer intelligent insights that are both detailed and actionable, allowing Sellers to introduce new products and engage with customers effectively. We leverage extensive structured and unstructured data to generate science-based insights about their business. Furthermore, we provide personalized recommendations tailored to individual Sellers' business objectives in a user-friendly format. These insights and recommendations are integrated into our products, including Amazon Brand Analytics (ABA), Product Opportunity Explorer (OX), and Manage Your Growth (MYG).
We are looking for a talented and passionate Principal Scientist to lead our research endeavors and develop world-class statistical and machine learning models. The successful candidate will work closely with Product Managers (PM), User Experience (UX) designers, engineering teams, and Seller Growth Consulting teams to provide actionable insights that drive improvements in Seller businesses.
Key job responsibilities
As a Principal Applied Scientist, you bring business and industry context to science and technology decisions.
You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms.
Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility.
You tackle intrinsically hard problems, acquiring expertise as needed.
You decompose complex problems into straightforward solutions.
We are open to hiring candidates to work out of one of the following locations:
New York, NY, USA | Seattle, WA, USA
BASIC QUALIFICATIONS
• Ph.D. in Computer Science, Mathematics, Statistics, related field, or equivalent experience.
• 10+ years of experience in applied science and software development at large scale.
• Experience building complex software systems that have been successfully delivered to customers.
• Extensive experience building predictive and optimization models.
• Expert knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, informational retrieval.
• Proven track record of leading and mentoring applied scientists.
• Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis.
• Proficiency in, at least, one modern programming language such as C, C++, Java, or Python.
• Ability to take a complex problem from scoping requirements through actual launch of the project.
• Excellent written and oral communication skills.
PREFERRED QUALIFICATIONS
• Experience in website optimization, recommender systems.
• Experience with distributed machine learning systems with billions of data points.
• 10+ years of hands-on experience in predictive modeling and analysis.
• Significant peer reviewed scientific contributions in premier journals and conferences.
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
• Significant peer reviewed scientific contributions in premier journals and conferences.
• Proven track record leading, mentoring, and growing teams of scientists
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 $159,100/year in our lowest geographic market up to $309,400/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. Applicants should apply via our internal or external career site.
Created: 2024-06-29
Reference: 2493418
Country: United States
State: Washington
City: Seattle
ZIP: 98109
About Amazon
Founded in: 1994
Number of Employees: 1600000
Website: https://www.amazon.com/
Career site: https://www.amazon.jobs/en/
Instagram: https://www.instagram.com/amazon/
LinkedIn: https://www.linkedin.com/company/amazon/
Facebook: https://www.facebook.com/Amazon
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