Sr. Capacity Planner OTR, OTR Planning - Osasco | Amazon Job

Job Description

About the Team
Trans Execution BR is a team that explores new approaches and ways of working at Amazon Logistics, offering scalable solutions to operate increasingly complex and growing last mile delivery networks. Trans Execution BR is responsible for critical processes such as Capacity Planning, Scheduling, Forecasting, and On Road Management, with the vision of continuously transforming these processes in a scalable manner.
In Brazil, we are building the OTR Capacity Planning team and are looking for a Sr Capacity Planning – OTR to raise the bar in this expansion.
About the Role
We are seeking a Program Manager for the Trans Execution BR team to drive strategic programs and optimize OTR Capacity Planning across Brazil. Thriving in an environment of high ambiguity, you will Think Big and Invent and Simplify processes to boost productivity at AMZL delivery stations. By analyzing OTR Capacity and channel flexibility to cover gaps based on volume fluctuations, you will make high-impact, data-driven decisions. Cultivating strong relationships with cross-functional peers across Hub, DSP, Flex, AMXL and EDSP Program team, Finance and ACES will be essential to align our network in the optimal cost and service level.
The impact of this position is tremendous, making decisions that will affect the entire country’s network of one of the largest companies in the world. A proven track record of sound judgement is a must. At Amazon, you will be encouraged to use this judgement as you grow and nurture your career.


Key job responsibilities
In this role, you will partner cross-functionally with Last Mile Channels, Supply Chain, Finance, Operations, and BI to transform several inputs that influence OTR (on-the-road) into precise, cost-optimal route and channel mix optimal plans on a daily cadence. You will lead the localization of OTR Capacity optimization in Brazil, managing multiple complex projects while seamlessly bridging gaps between systems, processes, and teams.
• Predictive Modeling & Gap Resolution: Design, build, and refine quantitative models to accurately predict On-the-Road (OTR) capacity gaps. Develop scalable, data-driven solutions and utilize channel flexibility to proactively close these gaps during volume fluctuations.
• Strategic Program Management: Lead and execute strategic programs for the Trans Execution BR team, taking ownership of optimizing end-to-end OTR Capacity Planning across the Brazilian AMZL network.
• Cross-Functional Leadership & Alignment: Cultivate strong, collaborative relationships with key stakeholders across Hub, DSP, Amazon Flex, AMXL, the EDSP Program team, Finance, and ACES. Drive alignment across these teams to execute capacity plans that achieve optimal cost structures while maintaining high service levels.
• Data-Driven Decision Making: Conduct deep-dive analyses on OTR capacity metrics and channel performance. Leverage this data to make high-impact, strategic decisions that balance network productivity with delivery execution.
• Process Innovation & Simplification: Navigate an environment of high ambiguity by applying Amazon’s "Think Big" and "Invent and Simplify" leadership principles. Identify operational bottlenecks and re-engineer capacity planning processes to significantly boost productivity at delivery stations.
• Performance Monitoring & Reporting: Continuously monitor network capacity health, track the effectiveness of implemented gap-solving strategies, and present actionable insights and progress reports to senior leadership.

Basic Qualifications
• Bachelor's degree in computer science, engineering, analytics, mathematics, Operations Research, statistics, IT or equivalent
• Speak, write, and read fluently in English and Portuguese
• Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
• 3+ years of professional experience in demand planning, statistical forecasting, supply chain analytics, or inventory modeling.
• Strong foundational knowledge of statistical forecasting methods (e.g., moving average, exponential smoothing, ARIMA) and historical data analysis.
• Experience with data analysis
• Proven ability to translate complex statistical concepts into actionable business insights for non-technical stakeholders in Sales, Marketing, and Operations.
• Proven experience in program or project management


Preferred Qualifications
• Master’s degree in Data Science, Applied Mathematics, Supply Chain Management, or an MBA with a quantitative focus.
• Proficiency in Python or R specifically for building, tuning, and deploying custom predictive forecasting models and time-series analysis.
• Strong SQL skills for querying and manipulating relational databases, combined with experience building dashboards in modern BI tools (e.g., Tableau, Power BI, Looker).
• Demonstrated experience applying Machine Learning (ML) and Artificial Intelligence (AI) techniques to supply chain variables, such as promotional modeling, cannibalization analysis, or new product launch forecasting.
• Active industry credentials such as APICS (CPIM, CSCP) or IBF Certified Professional in Forecasting (CPF).
• Experience owning or heavily influencing the S&OP (Sales and Operations Planning) cycle and a track record of driving measurable improvements in forecast accuracy metrics (e.g., MAPE, WMAPE, Bias)
• Experience implementing repeatable processes and driving automation or standardization;

Basic Qualifications:

- Bachelor's degree
- Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
- Experience defining program requirements and using data and metrics to determine improvements
- Experience in project management
- Experience working cross functionally with tech and non-tech teams
- Experience in defining and implementing process improvement initiatives using data and metrics
- Experience in Business English skills, both verbal and written

Preferred Qualifications:

- Experience in stakeholder management, dealing with multiple stakeholders at varied levels of the organization
- Experience in driving end to end delivery, and communicating results to senior leadership

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