AmazonScience_EchoBuds_01.jpg
In the second-generation Echo Buds, Amazon engineers were able to produce a device that is 21 percent smaller than the first version, while maintaining costs, through a multitude of innovations and integration of components.

How the second-gen Echo Buds got smaller and better

Take a behind-the-scenes look at the unique challenges the engineering teams faced, and how they used scientific research to drive fundamental innovation.

Notebook computers, tablets, and smartphones get the tech headlines, but these are largely mature products at this point. Smaller, more personal devices are going through a torrent of iteration and innovation.

Bluetooth wireless headphones are a highly competitive category, with products with bare-bones features available for less than $50, and feature-packed devices available at prices ranging all the way up to $400.

The first Amazon Echo Buds appeared in 2019, and, the follow-up second-gen Echo Buds in April 2021. The team at Amazon improved the second-gen earbuds in almost every way. This is a behind-the-scenes look at the unique challenges the engineering teams faced in creating the latest generation Echo Buds, and how they used scientific research to drive fundamental innovation to overcome those challenges.

Ultimately, Amazon’s team was able to a deliver feature-rich product that competes with products at the high end of the price range for $120.

Atif Noori was the principal product manager for both generations of Echo Buds. Reflecting Amazon’s customer focus, he said the process of designing the latest Echo Buds began with understanding the desires of the customer.

“We work backwards from the customers and build out a set of product requirements. From there we work across multiple talented teams to deliver a lovable product,” he said.

What customers want is great audio, a comfortable fit, long battery life, and excellent connectivity with their smartphones. Of course, many of these are in tension with one another. At the high end of the hearables category, customers also want advanced features like noise cancellation and cloud-based voice services like Alexa.

Echo Buds, Glacier White, Outside.jpg
For the second-generation Echo Buds, engineers worked to redesign the main Bluetooth chip and the audio co-processor in such a way that those two components could perform the tasks of five different components in the first-generation device.

Given this catalog of customer expectations, the nugget-sized wireless earbuds are giants of engineering challenges.

Reducing size to improve comfort and fit, while still maintaining connectivity performance, staying under comfortable temperatures limits, and meeting the customer’s battery life expectations with more features, was a challenge, but one the engineering team said they were excited to tackle.   

Milos Jorgovanovic, principal system architect at Amazon Lab 126, says size and cost are the constant constraints. The Amazon engineers were able to produce a device that is 21 percent smaller than the first version Echo Buds, while maintaining costs, through a multitude of innovations and integration of components.

This began with the processors, or, to use the engineers’ lingo, the silicon, which are the heart of the device. To make the device smaller, the engineers needed to reduce the size of the battery. Easily enough done on its own, except the team also needed to do this without reducing the device's battery life.

"And really for that, the key piece is the power consumption of the silicon platform itself," Jorgovanovic said. "At the same time, we are basically trying to offer high-end features at a much lower power consumption and lower cost."

For the second-generation Echo Buds, team worked with manufacturers to redesign the main Bluetooth chip and the audio co-processor in such a way that those two components could perform the tasks of five different components found in the first-generation device.

"We basically cut the power consumption for audio and Alexa processing by at least a factor of two from what it was before," Jorgovanovic said.

We basically cut the power consumption for audio and Alexa processing by at least a factor of two from what it was before.
Milos Jorgovanovic

This was done while simultaneously improving the Alexa’s ability to hear customers speak.

Amazon started the voice category with the original Echo and Alexa launch in November 2014, so it makes sense that the latest Echo Buds would offer seamless Alexa functionality. With Alexa, a user can not only play music and make phone calls, but also set reminders, request information, and in certain cities, plan public transportation routes and get information on the train or bus they're hoping to catch, all while leaving their phone in their pocket.

"If a customer wants to take Alexa on the go, they can do that and have the same experience as they do with an Echo in their home," Noori said. "It's even more than that though. The responses are tailored for when you're on the go. For example, you can ask Alexa to remind you to buy tahini when you arrive at Whole Foods. And in some stores, you can then ask Alexa if tahini is in stock, or ask which aisle the tahini is on, which is pretty awesome.”

Achieving all of that requires not only integration with the cloud, but also a good bit of on-device processing. Jorgovanovic said improvements in the new processor allowed this to be done with less power consumption.

"We put a better digital signal processor in there, but the second, and more important piece, is that this chip was designed so that it allows very aggressive frequency and voltage scaling," he said. "What it means is that if the device is basically sitting in the air, doing very little processing, we are able to lower both the frequency and the voltage on that chip and have the chip consume much less energy."

If the user speaks and, for example, asks a friend, "Hey, Jason, how are you doing?" the device will run a small amount of processing to determine if the user said "Alexa." If the user did say "Alexa," the digital signal processor (DSP) is boosted even further, increasing the voltage, boosting the frequency, and engaging in more complex compute. At that point the device is processing the Alexa event — the information is sent to the cloud and then the response is played when it is received.

"We basically have these levels of processing, and we set the frequency and the voltage on the processor to the adequate level for the amount of processing we need. This is one of the two main things that we've done in gen two to scale down the power consumption,” Jorgovanovic explained. “The second big thing was integrating more functionality into the main Bluetooth SoC [system on a chip] by innovating on the Bluetooth protocol between the two earbuds, which reduced the number of components and power spent on interconnect. Overall, we reduced total device power by more than 35 percent relative to the first Echo Buds, and specific to that DSP processing for audio and Alexa, by at least a factor of two, if not more. And that's just, wow."

Reducing the power of the processors brought another benefit: reduced heat. "Because we pack in so much, we have to factor in heat dissipation," Noori said.  "It was not like you can add on cooling fins or a big heat sink. It required careful simulation and design."

Beyond the silicon, another major constraint in size and cost are the antennas.

Connectivity is a hurdle in wireless Bluetooth headphones because they are partially hidden in the ear. And while ears can block frequencies, the human body is also effective at blocking signals. The user's smartphone needs to connect with one of the earbuds, and then the two earbuds need to send packets to each other, with as little latency as possible.

"That's really important — the synchronization of the two ear buds — because our hearing is very sensitive to this," Jorgovanovic said. "Something like a hundred microseconds of delta between left and right can easily be felt. And, the effect is the user will sense that the audio is not coming from straight ahead, but instead coming from one side or the other."

Balamurugan Shanmugam, senior antenna design engineer, says the connectivity issues are a challenge for all wearable devices.

"This is an inherent physics problem, right? I mean, this is not unique to Amazon. Anyone working on body-worn devices or even looking just at medical devices such as wireless-enabled pacemakers will encounter the same problem," he said.

Shanmugam's challenge was to improve connectivity in a smaller package. His team's first go at the problem developed a solution, but the manufacturing costs were too high. It was time to develop a novel solution.

Just as the engineers were able to reduce the number of processors in the device, they also were able to integrate functions to accommodate a new antenna. The best location for the antenna is in the front center of the device, but that is also where a user expects to tap or use gestures. On the first-generation Echo Bud, the touch sensor and electrostatic discharge (ESD) circuits were utilizing the location an antenna needs to maximize wireless performance. To address that, the engineers invented an integrated antenna design that combines the antenna, touch, and ESD subsystems.

"The newest Echo Bud has integrated antenna, touch, and electrostatic discharge to optimize wireless performance," Shanmugam said.

Noori said that connectivity is among the features that stand out in the latest Echo Buds. "Connectivity is very solid on these devices; I'm definitely proud of the connectivity performance. I think we nailed that."

And there’s more to come.

"I think there's a lot of interesting things that can be done with earbuds that are outside of basic music playback," Noori said. "We’re continuing to innovate on behalf of our customers, and pushing out software updates. Echo Buds will continue to get better and smarter over time."

Get them in black or white with a wired charing case for $119.99 or with a wireless charging case for $139.99.

Research areas

Related content

US, NY, New York
We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
US, CA, San Francisco
Join our Frontier AI & Robotics team to support the hardware integration of next-generation robotic systems that will transform how robots perceive and interact with the world. You'll take ownership of hands-on hardware assembly, software integration, and system validation tasks across advanced actuators, precision sensors, and robotic subsystems — ensuring they work seamlessly together to support breakthrough AI research and real-world deployment. Key job responsibilities - Assembly, Integration & DFx — Assemble and integrate robotic hardware (actuators, sensors, vision systems, machined components). Execute assembly processes and test protocols developed with engineering. Provide DFM/DFA feedback and perform simple mechanical/electrical/software design tasks; support integration/debug and partner with engineers to optimize manufacturability and testability. - R&D Prototype Test & Validation — Validate hardware revisions, verify mechanical assemblies, power sequencing, communication interfaces, and peripherals during bring-up. - Debugging & Failure Analysis — Troubleshoot and root-cause issues across the robotic platform (power, compute, comms, actuators, sensors). Conduct failure analysis from component to system level. Reproduce critical failures, interpret schematics, and bridge communication between the lab and engineering teams. - Technical Documentation — Author and maintain runbooks, failure analysis reports, assembly guides, and troubleshooting guides; uphold consistent documentation standards across the lab. - Mechanical Design Support — Perform simple R&D design tasks and test fixture design in CAD, ensuring quality and alignment with engineering priorities. - Lab Operations Support — Support machine shop capabilities, equipment maintenance, inventory management, vendor coordination, and safety/regulatory compliance. - Test Capability Development — Develop test methodologies, design jigs/fixtures, support hardware-in-the-loop (HIL) testing, and streamline failure-to-resolution workflows. A day in the life Your focus centers on the hardware and software that powers our advanced robotic platforms. You'll execute high degree-of-freedom (DoF) robotic prototype assembly and validation, working alongside engineers and fellow technicians. Your responsibilities include building, debugging, validating prototype, performing critical component and assembly quality assessments, providing DFM/DFA feedback to engineers, and designing test jigs and fixtures. Throughout the day, you balance complex assemblies and integration testing while handling urgent prototyping requests, documentation updates, and preparation for upcoming milestones. You're switching between working at the bench, collaborating in design reviews with engineers, and ensuring lab safety and equipment maintenance. About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
US, CA, San Francisco
Join Amazon's Frontier AI & Robotics team as a Member of Technical Staff, this Technical Program Manager will become the driving force behind breakthrough robotics innovation. You'll orchestrate complex, cross-functional programs that bridge AI research, software, hardware, and production deployment—managing the technical workstreams that enable robots to see, reason, and act in Amazon's warehouse environments. Your program leadership will directly accelerate our mission to build the next generation of embodied intelligence. Key job responsibilities · Establish and drive program management mechanisms and cadence for complex robotics and AI development initiatives spanning research, software engineering, hardware, and operations · Manage end-to-end program execution across the full robotics stack—including AI models, software engineering, and hardware deployment · Drive decision-making velocity by facilitating tradeoff discussions when there are conflicting priorities; determine whether decisions are one-way or two-way doors · Own program-level risk management, proactively identifying technical, schedule, and resource risks; escalate where necessary and drive mitigation strategies · Manage dependencies and scope changes across internal teams and partner organizations, ensuring alignment on commitments, timelines, and technical requirements · Create transparency through clear RACI frameworks, program dashboards, and communication mechanisms that keep stakeholders aligned on status, risks, and decisions · Exercise strong technical judgment to influence program-level decisions on deployment methodology, scalability requirements, and technical feasibility—acting as the voice back to research and engineering teams · Build sustainable program management processes that scale as our organization grows, adapting agile frameworks to the unique challenges of AI robotics A day in the life Your focus centers on driving velocity and alignment across our robotics programs. You might start your morning facilitating tradeoff decisions between AI researchers and software engineers on a critical prototype milestone, then transition to managing dependencies across hardware and operations teams to keep timelines on track. In the afternoon, you could be conducting risk assessments on supply chain constraints that impact our development roadmap, updating program dashboards to provide leadership visibility, or working with partner teams to align on deployment strategies. You'll establish the mechanisms and cadence that keep our fast-moving organization synchronized—from sprint planning rituals to cross-functional design reviews. Throughout the day, you balance hands-on program execution with strategic escalation, ensuring technical decisions align with our long-term vision while removing obstacles that slow teams down. You're the connective tissue that enables researchers, engineers, and operations specialists to move fast together. About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
US, CA, San Francisco
About the Role: We are looking for a Member of Technical Staff - Mechanical Engineer with a passion for building complex robotic systems from the ground up. This role is ideal for someone with a deep understanding of structural and electromechanical design, who thrives in hands-on environments and has experience taking high-performance robots from concept to production. You will work on the mechanical and system architecture of advanced robotics platforms, including high degree-of-freedom systems, where considerations such as actuator selection, thermal constraints, cabling, sensing integration, and manufacturability are critical. This is a cross-disciplinary role requiring close collaboration with electrical, software, and AI research teams. Beyond day-to-day hardware development, this role also provides exciting avenues to contribute to innovative research projects. Whether you’re interested in mechatronics, sensor integration, or novel actuation methods, you’ll find opportunities to explore your research interests while building real-world systems that advance in the field of high degree-of-freedom robotics. What You Bring: * A systems-thinking mindset with a strong grasp of cross-domain engineering tradeoffs. * A bias toward action: comfortable building, testing, and iterating rapidly. * A collaborative and communicative working style — especially in multi-disciplinary research environments. * A passion for robotics and advancing the state of the art in intelligent, capable machines. Key job responsibilities * Lead mechanical design of robotic subsystems and full platforms, including structures, joints, enclosures, and mechanisms for a research environment. * Own kinematic, dynamic, and structural analyses to guide the design and optimization of full systems and subsystems of high-DoF robots * Specify and integrate actuators and motors for high-torque density applications in high-degree-of-freedom systems. * Contribute to thermal management strategies for motors, sensors, and embedded compute hardware. * Integrate sensors such as lidar, stereo cameras, IMUs, tactile sensors, and compute modules into compact, functional assemblies. * Design and route cabling and wire harnesses, ensuring reliability, serviceability, and thermal/electrical integrity. * Prototype and test mechanical systems; support hands-on builds, debug sessions, and field testing. * Conduct root cause analysis on system-level failures or performance issues and implement design improvements. * Apply Design for Manufacturing (DFM) and Design for Assembly (DFA) principles to transition prototypes into scalable builds (10s–100s of units). * Collaborate with cross-functional teams in electrical engineering, controls, perception, and research to meet research and product goals. About the team Frontier AI & Robotics (FAR) is the team at Amazon building the next generation of embodied intelligence. FAR drives the development and implementation of advanced AI models within Amazon’s operations that enable robots to see, reason, and act on the world around them, supporting a number of different warehouse automation tasks.
US, CA, San Francisco
Join Amazon's Frontier AI & Robotics team and help shape the future of intelligent robotic systems from the inside out. As a Member of Technical Staff - Firmware Engineer, Electronics, you will develop the low-level firmware that brings our in-house robotic actuators to life—writing the embedded code that bridges sophisticated hardware and the high-level AI control systems that power our next-generation robots. Your work will directly enable our robots to see, reason, and act in real-world warehouse environments, making you a critical contributor to one of the most ambitious robotics programs in the world. Key job responsibilities • Develop, test, and optimize embedded firmware for custom in-house robotic actuators, including motor control algorithms (FOC, commutation, current/torque/speed/position loops) running on microcontrollers and DSPs • Design and implement real-time firmware for actuator state estimation, fault detection, and protection logic, ensuring robust and safe operation across all actuator variants deployed in FAR's robotic systems • Collaborate with electronics engineers and motor design engineers to define firmware requirements, hardware interfaces (SPI, I2C, CAN, EtherCAT, RS-485), and actuator bring-up procedures for new hardware revisions • Develop and maintain firmware for field-oriented control (FOC) and sensored/sensorless motor commutation, including tuning current regulators, velocity controllers, and position controllers for high-performance robots • Build and maintain firmware test frameworks and hardware-in-the-loop (HIL) test environments to validate firmware behavior across actuator operating conditions, edge cases, and failure modes • Partner with controls engineers and AI researchers to ensure firmware-level interfaces support high-bandwidth, low-latency communication required by whole-body control and motion planning algorithms • Contribute to actuator firmware architecture decisions, define software-hardware interface standards, and maintain firmware documentation and version control practices to enable scalable multi-actuator development • Support rapid hardware bring-up and debugging of new actuator prototypes, leveraging oscilloscopes, logic analyzers, and custom diagnostic tools to characterize and validate firmware behavior on novel hardware A day in the life Your day is rooted in the intersection of hardware and software where you’ll be wiring firmware from scratch to control custom motors. You might start your morning reviewing firmware behavior logs from the previous night's actuator characterization runs, then spend time working alongside motor design and electronics engineers to debug a torque ripple issue in the motor control loop. In the afternoon, you could be writing and validating embedded firmware for a new actuator variant, tuning (field-oriented control) FOC algorithms, and collaborating with the controls team to ensure firmware interfaces align with high-level motion planning requirements. Beyond the bench, you'll participate in architecture reviews with hardware and software engineers, contribute to code reviews, and document firmware specifications that enable smooth hardware handoffs. You'll be working on actuator variants—each with unique power, torque, and speed requirements—and you'll be the firmware voice in cross-functional design discussions that shape how our actuators are built and controlled. The pace is fast, the problems are novel, and the impact is direct. About the team Frontier AI & Robotics (FAR) is the team at Amazon building the next generation of embodied intelligence. FAR drives the development and implementation of advanced AI models within Amazon’s operations that enable robots to see, reason, and act on the world around them, supporting a number of different warehouse automation tasks.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists in the Forecasting, Macroeconomics & Finance field document, interpret and forecast Amazon business dynamics. This track is well suited for economists adept at combining times-series statistical methods with strong economic analysis and intuition. This track could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models. Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon, including retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. The Forecasting, Macroeconomics & Finance field utilizes methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term. We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues and further delight customers.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.