LatAm Business Intel Engineer, Amazon Leo LATAM Consumer

Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency high-speed broadband connectivity to unserved and underserved communities around the world. The Amazon Leo Latam Consumer team is looking for a talented individual to lead data science and analytics that will support key decisions for consumer business development. This role is responsible for analyzing large sets of data and building pipeline for automated dashboards and reporting. A successful candidate will be independent comfortable with ambiguity and adept at dealing with large volumes of data including geo-spatial data. We are looking for someone who has built end-to-end analytical workflows has experience in data visualization and is obsessed with driving insights on statistically sound data.

This position may require access to information technology or hardware that is subject to export control laws and regulations including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Employment in this position is contingent upon obtaining any required export licenses or other approvals from the United States government. As such the successful candidate must be eligible to obtain any necessary export licenses or approvals based on their nationality citizenship and any other factors considered by the applicable export control regulations.

Key job responsibilities
large data sets to identify patterns understand drivers and generate insights for demand retention service plan mix and seasonality models
queries to extract data and insights combining datasets within Leo using available datasets
build and maintain automated reporting dashboards and recurrent analysis in support of data driven decisions across business operations
opportunities for automation to accelerate insight generation
and create visualization of large geo-spatial data to drive subscriber growth strategies
Amazon systems and tools to effectively work with process and analyze large datasets
comprehensive written strategy documents considering different types of data and inputs across a broad range of stakeholders

- 5 years of developing automated reporting experience
- 5 years of SQL experience
- Experience programming to extract transform and clean large (multi-TB) data sets
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval data science machine learning and data mining

- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing analyzing and communicating results to senior leadership

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