Sobre

• Do you feel the challenge and the adrenaline kick when a huge data-set stares
• you in the face and you know that somewhere inside are hidden very important
• business insights that can fundamentally alter the way top business leaders
• think and act? Do you enjoy presenting strong data backed insights to business
• leaders; insights that can topple their long held beliefs and compel them to
• change their direction completely? If yes, then you are the one we are looking
• for.
• We are looking to invite passionate leaders, with expertise in generate power
• business insights from very large datasets, on a journey where the primary aim
• would be to enable needle moving business impacts through statistical analysis.
• We are looking for leaders who can envision the design and development of
• analytical infrastructure which can support strategic and tactical
• decision-making. Those who join this high visibility team would have to navigate
• through significant ambiguity in defining business problems and converting them
• to analytical problems.
• This role requires additional exposure and experience to Machine Learning.

• Key job responsibilities
• • Use machine learning and analytical techniques to create scalable solutions
• for business problems
• • Analyze and extract relevant information from large amounts of Amazon’s
• historical business data to help automate and optimize key processes
• • Design, development, evaluate and deploy innovative and highly scalable models
• for predictive learning
• • Research and implement novel machine learning and statistical approaches
• • Work closely with software engineering teams to drive real-time model
• implementations and new feature creations
• • Work closely with business owners and operations staff to optimize various
• business operations
• • Establish scalable, efficient, automated processes for large scale data
• analyses, model development, model validation and model implementation
• • Mentor other scientists and engineers in the use of ML techniques
• • Innovate with the latest GenAI technology to build highly automated solutions
• for efficient customer promotions
• • Design, develop and deploy end-to-end machine learning solutions in the Amazon
• production environment to delight Amazon customers
• • Collaborate with cross-functional teams to develop comprehensive
• ML/statistical models that can scale to millions of customers to multiple
• countries

• About the team
• Brazil Payments is part of the International Emerging Stores Payments team and
• focuses on supporting the launch of new payment and financial products to our
• customers in Brazil. Basic Qualifications: - Experience working as a Data
• Scientist
• - Experience with data scripting languages (e.g. SQL, Python, R etc.) or
• statistical/mathematical software (e.g. R, SAS, or Matlab)
• - Experience with machine learning/statistical modeling data analysis tools and
• techniques, and parameters that affect their performance
• - Master's degree in computer science, engineering, mathematics or equivalent,
• or experience in a ML or data scientist role with a large technology company
• Preferred Qualifications: - Experience with AI/ML technologies
• - PhD in Computer Science, Computer Engineering, or related fields
• - Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce,
• and Hive)
• - Experience in defining and creating benchmarks for assessing GenAI model
• performance
• - Experience working on multi-team, cross-disciplinary projects
• - Experience applying quantitative analysis to solve business problems and
• making data-driven business decisions

• 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
• [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.