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  • Senior Data Scientist, Amazon Finance AI

    Amazon (Seattle, WA)



    Apply Now

    Description

    Own the data science elements of Amazon's Financial Transformation Programs including various financial AI based products to help with data-based decision making, workflow performance optimization, and financial insight related product performance tracking. Work directly with product managers and engineering team to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data science requirements, plan experiments and proof of concepts to identify online and offline metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.

    Key job responsibilities

    You are considered a data science leader on your team. You take the lead on large projects and drive solutions to complex or ambiguous problems. You design solutions that help us take advantage of business opportunities (new and existing). You may own the delivery of data science solutions for an entire business application. You are a key influencer of your team’s business strategy are able to influence the strategies of related teams. You work efficiently and routinely deliver the right things with limited guidance.

     

    You have broad expertise in a variety of data science disciplines. You use this knowledge to recommend the right data science strategy and methods. You are able to evaluate cross-team perspectives and understand how interactions among teams, processes, and software systems need to be modelled in solutions. You investigate new and novel methods without being guided through them. You use quantitative methods to derive justification and build consensus for the required level of analyses to meet goals. You advocate for measurements, sensors, and/or relevant metadata. You show good judgment when making trade-offs between short-term customer, market, or research needs and long-term operations or technology needs. You make appropriate technical and science methodology trade-offs.

     

    A day in the life

    A Data Scientist III pays crucial role in team development by driving data science and operational best practices. They review analyses, code, and data modeling processes for other data scientists and economist (both junior and senior) and provide constructive feedback. They give internal presentations to help raise awareness of new and well-established econometric and machine learning techniques. They continue to develop their own knowledge by staying abreast of current data science research. They help recruit and interview for the team and confidently train new members about Finance customers, how Forecasting team’s solutions work, and how those solutions are reflected in the data.

     

    About the team

     

    You will be part of Range (Research and Applications for Next-Gen Economics) team that builds AI-native foundations for Amazon's financial systems, purpose-built for Global Finance Customers and designed to scale across Amazon.

     

    Our solutions include headcount reporting, people cost forecasting, allocation of fixed and variable costs, and CFO level reporting. We also provide support to Global FP&A and Finance organizations, and critical financial workflows.

    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

    - Bachelor's degree

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

    Preferred Qualifications

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

     

    - Experience managing data pipelines

     

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

     

    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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