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  • Data Scientist, TSI Science

    Amazon (Seattle, WA)



    Apply Now

    Description

    As we strive to be Earth's most customer-centric company, Amazon has reinvented how hundreds of millions of people shop online – providing customers with the opportunity to find and discover virtually anything they want to buy and providing millions of sellers with a platform for growing successful businesses. We are looking for an exceptional data scientist to help us develop new ways to build trust and loyalty with sellers, a crucial component of our flywheel.

     

    Sellers' trust in Amazon is our top priority and in this role, you will be tasked with uncovering actionable insights and building predictive models that drive seller trust and satisfaction. Amazon's growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems through advanced analytics.

     

    The successful candidate will be a self-starter, comfortable with ambiguity and be able to translate business problems into analytical solutions. They excel at statistical analysis, machine learning, and data visualization, and can partner effectively with business leaders to derive meaningful insights that drive decision-making. They will develop predictive algorithms to solve complex business challenges. They will also be required to communicate technical findings to non-technical stakeholders and drive data-driven decisions. They are analytical and creative, and don't quit. This is a role with high visibility to senior leadership and with high opportunity for impact for those willing to roll up their sleeves and dive deep to achieve results.

    Key job responsibilities

    As a Sr. Data Scientist at Amazon, you'll work with vast datasets to drive insights that influence key business decisions, providing technical leadership to cross-functional teams of scientists, product managers, and engineers.

     

    Your expertise in machine learning, advanced analytics, and data visualization will be essential in transforming complex data into actionable business intelligence. This role demands both technical excellence and business acumen, as you'll own the complete lifecycle of analytical solutions - from conception to implementation and optimization.

    You'll be instrumental in:

    - Developing sophisticated machine learning models and analytical frameworks

     

    - Creating scalable solutions that enable data-driven decision making

     

    - Leading strategic initiatives through quantitative analysis and insights

     

    - Collaborating with stakeholders to identify and implement process improvements

     

    - Building and maintaining analytical tools that drive business efficiency

     

    This position offers significant opportunity to shape strategic decisions through data-driven insights, working closely with business leaders to solve challenging problems at scale.

    About the team

    Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.

     

    You will be working within a dynamic, diverse, and supportive group of scientists who share your passion for innovation and excellence. You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.

    Basic Qualifications

    - 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

    - 4+ years of data scientist experience

    - Experience with statistical models e.g. multinomial logistic regression

     

    - Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

    Preferred Qualifications

    - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience

     

    - Experience managing data pipelines

     

    - Experience working with data engineers and business intelligence engineers collaboratively

     

    - Experience as a leader and mentor on a data science team

     

    - Master's degree

     

    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 $143,300/year in our lowest geographic market up to $247,600/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.

     


    Apply Now



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