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Description

We are looking for a highly motivated Software Development Engineer in building top-notch Seller facing analytics applications to provide actions first insights which are aimed to improve selling partners' business. If you are passionate about being a part of a high performance team, working in full stack environment along with data and machine learning models, our team is perfect fit for you. You will experience challenging and innovative opportunities, and will be motivated to deliver the best customer experience.

Key job responsibilities

Participate in the design, development, implementation, testing and documentation of large-scale distributed software applications, tools, systems and services. Opportunities to work for full stack env, including back end, front end, big data and machining learning models. Evaluate and make decisions around the use of new or existing software products and tools. Mentor junior development engineers.

About the team

SG&D is the growth and development engine for Amazon Selling Partners (SPs) WW. Leveraging science partnerships across Amazon, 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.

SG&D amplifies the growth trajectory of any Selling Partner WW through scaled and self-service software solutions. To achieve that, we provide SPs with ground truth data about what end-customers seek, leverage science to create insights about their businesses, and produce recommendations on where opportunity exists, in a unified and seamless experience. One of the products is Amazon Brand Analytics (ABA), which helps SPs understand their Amazon businesses, the competitive landscape, their traffic/search performance, their customers and how they benchmark against peers.

Basic Qualifications

- 3+ years of non-internship professional software development experience

- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

- Experience programming with at least one software programming language

Preferred Qualifications

- Bachelor's degree in computer science or equivalent

- 1+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience

- Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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.