Data Scientist, Supply Chain Data Science

hace 3 semanas


Ciudad de México Amazon A tiempo completo
Data Scientist, Supply Chain Data Science

Are you a data enthusiast? Does the world’s most complex logistic systems inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the network we have today into the network we need tomorrow.

Amazon’s extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon’s data and generate actionable recommendations using optimization and simulation. Come build with us

In this role, your main focus will be to perform analysis, synthesize information, identify business opportunities, provide project direction, and communicate business and technical requirements within the team and across stakeholder groups. You consider the needs of day-to-day operations and insist on the standards required to build the network of tomorrow. You will assist in defining trade-offs and quantifying opportunities for a variety of projects. You will learn current processes, build metrics, educate diverse stakeholder groups, assist science groups in initial solution design, and audit all model implementation. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made.

The ideal candidate will have a strong ability to model real world data with high complexity and delivery high quality analysis, data products and optimizations models for strategic decision. They are excited to be part of, and learn from, a large science community and are ready to dig into the details to find insights that direct decisions. The successful candidate will have good communication skills and an ability to speak at a level appropriate for the audience, will collaborate effectively with scientists, product managers and business stakeholders.

Key job responsibilities
Statistical Models (ML, regression, forecasting, ) Optimization models, AB and hypothesis testing, Bayesian models. Communication skills with both tech and non tech stakeholders. Writting skills, capable to create documents for different types of readers (business, science, tech) to communicate results on analysis, testing.

A day in the life

We are open to hiring candidates to work out of one of the following locations:

Mexico City, DIF, MEX BASIC QUALIFICATIONS

- 3+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 3+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree in a quantitative field
- Experience applying theoretical models in an applied environment
- Fluent in written and spoken Spanish and English (b2+)

PREFERRED QUALIFICATIONS

- Experience in a ML or data scientist role with a large technology company

Posted: February 2, 2024 (Updated 4 days ago)

Posted: April 9, 2024 (Updated 10 days ago)

Posted: April 16, 2024 (Updated 11 days ago)

Posted: April 4, 2024 (Updated 21 days ago)

Posted: January 31, 2024 (Updated 23 days ago)

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

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