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Amazon Senior Data Scientist Tech Deployment Modeling 
United States, Tennessee, Nashville 
557001953

04.09.2024
DESCRIPTION

You will play a crucial role in developing advanced analytical models and solutions to drive excellence in field execution as Amazon prepares for robotic deployments at scale. You will collaborate closely with our team of engineers, data scientists, process experts, and operations personnel to identify opportunities for optimization, process improvements, and efficiency gains. You will develop and implement data-driven solutions, leveraging cutting-edge techniques in simulation and optimization. You will be a modeler and a builder, working with customers across Amazon Robotics global organization.Key job responsibilities
• Design and implement sophisticated analytical models, including queuing models (e.g., M/M/1, M/G/1, G/G/c) to analyze and optimize deployment operations.
• Lead the development of deterministic optimization models, such as linear programming (LP) and mixed-integer programming (MIP), to optimize resource allocation, scheduling, and planning
• Develop stock and flow models to simulate inventory management, supply chain dynamics, and resource allocation.
• Build network models (e.g., transportation models, assignment models, and network flow models) to optimize routing, scheduling, and resource allocation in logistics and distribution networks.
• Construct financial models (e.g., Monte Carlo simulations, option pricing models, and portfolio optimization models) to support decision-making in investment planning, risk management, and resource allocation.
• Implement and integrate developed models into existing systems and workflows to streamline processes, resource allocation, and improve operational efficiency.
• Leverage statistical techniques, machine learning algorithms, and optimization methods to extract insights (patterns, trends, correlations) from large, structured and unstructured datasets.
• Collaborate with engineering teams to validate model assumptions, calibrate models based on real-world performance, and refine models to account for dynamic industrial conditions.
• Participate in the ideation and development of new data science initiatives, contributing to the organization's strategic goals in optimizing industrial processes.


BASIC QUALIFICATIONS

- 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience
- Experience with statistical models e.g. multinomial logistic regression
- Experience in modeling and simulating complex systems that involve interdependencies, feedback loops, and dynamic interactions between various components.