Data Scientist I, Amazon 1P Credito, Payments

Data Scientist I, Amazon 1P Credito, Payments

Data Scientist I, Amazon 1P Credito, Payments

Amazon

45 minutos atrás

Nenhuma candidatura

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 with data scripting
  • languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g.
  • R, SAS, or Matlab)
  • - Experience as a data/research scientist, statistician or quantitative analyst
  • in an internet-based company with complex and big data sources
  • - Experience applying quantitative analysis to solve business problems and
  • making data-driven business decisions
  • - Bachelor's degree or above in Math, Statistics, Computer Science, or related
  • Science field Preferred Qualifications: - Master's degree in Science,
  • Technology, Engineering, or Mathematics (STEM)
  • - Experience working effectively with science, data processing, and software
  • engineering teams
  • 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.