The Transportation Volume Planning team owns and operates ML and simulation systems that continually optimize the distribution of tens of millions of products across Amazon’s warehouses in the most cost-effective manner, utilizing large scale optimization techniques and distributed computing in trying to reduce overall transportation costs while improving the customer experience. We are focused on saving hundreds of millions of dollars using big data technologies, cutting edge science, machine learning, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply.
We’re looking for a passionate and results-oriented Principal Analytics Manager who enjoys the challenge of diving into complex problems and solving the unsolvable to drive the key decisions. The person will lead the team of BIEs and DEs to develop large scale, fault tolerant and high availability data analysis systems.
Watch http://bit.ly/amazon-scot to get the big picture.
Key job responsibilities
In this role you will…
• Collaborate with and influence a wide set of stakeholders, providing thought leadership, product expertise, and business insight.
• Work across Transportation teams, PMs, Engineers, Scientists, Finance, and SCOT teams to establish the network planning Analytics Roadmap.
• Interface with cross-functional teams to build centralized tools that will allow for rapid defect detection and repair.
• Partner with Engineers and Software Engineers to design products and systems to enhance explainability of various machine learning and optimization models.
• Explore/analyze and work with Product Managers to understand customer behaviors, spot system defects, and benchmark our ability to serve our customers
• Design and implement technical solutions with an appropriate analytics strategy and data set design; make technical trade-offs for long-term / short-term needs; and drive best practices in operational excellence, data modelling, and analysis. This role will likely be a good fit for you if you currently…
• Are energized by nuanced problem statements, navigating complexity with thoughtful analyses, and delivering crisp findings and recommendations to leadership teams.
• Looking around corners to proactively identify and build automated, scalable analytical solutions
• Use analyses to propose innovative and profitable initiatives to senior management/executives.
• Analyze and synthesize large streams across multiple inputs.
• Find and create ways to measure the customer experience to drive outcomes.
• Curious to identify patterns in and how they relate to the outcomes • Inspire high performance from your team, with your vision, energy, high standards and results.
* Manage, mentor and grow a team of BIEs and DEs
About the team
About the team
The Transportation Volume Planning team is part of the Fulfillment Optimization org and owns optimization and simulation systems to guide Amazon's outbound capacity planning. The team is currently spread across Seattle, Austin, TX, and New York City. The team is multi-disciplined comprising of research science, business intelligence, and software development. Come join us as we fundamentally redesign our approach to Amazon first-party fulfillment.
Watch this video to learn more about our organization,
SCOT: http://bit.ly/amazon-scot
BASIC QUALIFICATIONS
- 7+ years of business intelligence and analytics experience
- 5+ years of delivering results managing a business intelligence or analytics team, including employee development and performance management experience
- Experience with SQL
- Experience with ETL
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software
PREFERRED QUALIFICATIONS
- 4+ years of working with very large data warehousing environment experience
- 10+ years of data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding experience
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