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Amazon Science Community and Machine Learning University call for proposals - Spring 2022

Making Amazon the best place in the world to do customer-obsessed science and engineering

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About this CFP

The Amazon Science Community and Machine Learning University teams are committed to making Amazon the best place in the world to do customer-obsessed science and engineering. Our programs, including onboarding bootcamps, mentorship programs, and instructor-led classes, help Amazon’s scientists and engineers do their best work. We aim to advance the state of the art in the design and execution of these programs. We are seeking to fund economics and social science research on the following topics:

  • Scientific productivity metrics – high quality science can take years to develop and have a customer impact; how can we know in the meantime if a research team is flourishing or floundering?
  • Scientific impact metrics – scientific work not only operates on long timelines, it has a cumulative effect.  One research paper may not get turned into a product or service, but it can serve as critical inspiration for the next research paper that does.  How can we assess the impact of a given research project, team, or individual, beyond basic tools like citation and patent metrics?
  • Team-based research success factors – impactful science is increasingly done by teams; research teams to create the science, and engineering teams to implement scientific solutions on behalf of customers.  What are the most critical factors that cause a team to have scientific success, and what mechanisms can influence them?
  • Individual-based research success factors – what are the key factors to individual scientific success, and which of these are a product of the institutional environment?  How can we optimize the physical and social environment to allow scientists to do their best work?
  • Educational design – what drives success in technical courses when presented in-person, live remote, or self-paced?  What drives students to choose one option or the other, and how can we leverage hybrid formats to bring together the strengths of each of these?  What are the data-driven best practices for online education, particularly with regards to recent shifts in working practices?  How do we measure practical success when teaching scientific knowledge at scale?

Timeline

Submission period: June 3 - July 8, 2022

Decision letters will be sent out December 2022

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, no more than $80,000 USD
  • AWS Promotional Credits, no more than $20,000 USD
  • Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-year unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.

Eligibility requirements

Please refer to the ARA Program rules on the FAQ page.

Proposal requirements

Proposals should be prepared according to the proposal template.

PIs should either include plans for open source contributions or state that they do not plan to make any open source contributions (data or code) under the proposed effort.

Selection criteria

ARA will make the funding decisions based on the potential impact to the research community and quality of the scientific content.

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

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Robotics/AI Motor Control Scientist, Fauna
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.
Applied Scientist III, Sponsored Products Marketplace Intelligence
US, WA, Seattle
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are the Sponsored Products - Marketplace Intelligence (MI) team. We are looking for an Applied Scientist to help build production ML and bandit solutions to customize the search experience. We determine which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of machine learning, causal inference, and optimization techniques to continuously explore, learn, and optimize the allocation and ranking of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. You will be on the Search Ad Ranking and Interleaving team org - specifically the team that focusses on whole page optimization. Our mission is to personalize and contextualize SP ad allocation on the entire search page. We do this by modeling shopper responses to the number, placement, and quality of ads. We are a data- and hypothesis-driven organization that uses online experimentation, simulation, causal modeling, and online feedback to place ads where they’re useful to shoppers and provide improved discoverability and sales for advertisers. This is a unique opportunity for someone who wants to have broad business impact, a direct impact on customers and the search experience, and get broad exposure to a wide range of scientific techniques (machine learning, bandit learning, optimization, LLMs). We are looking for an Applied Scientist to join Interleaving team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. We’d like someone with practical experience with LLMs / GenAI for production to improve how we rank and allocate ads on the page today. If you thrive in a product-focussed and data-driven environment, then this role is for you. As a Applied Scientist on this team, you will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, product managers, software engineers and TPMs. You will have opportunity to design, run and analyze / experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities * Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. * Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. * Develop efficient algorithms for multi-objective optimization and AI control methods to find operating points for the ad marketplace then evolve them * Be an expert at designing and implementing solutions that use a range of data science methodologies to automate data analysis or to solve complex business problems. * Perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experience, without compromising Ad revenue in addition to designing metrics for complex systems. * Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity. * Run A/B experiments, gather data, and perform statistical analysis.
Applied Scientist, Last Mile
US, WA, Bellevue
Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.
Applied Scientist II, Alexa International Team
US, WA, Bellevue
Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Set up experimentation frameworks for agile model analysis and A/B testing. * Collaborate with partner teams on LLM evaluation frameworks and post-training methodologies. * Contribute to end-to-end delivery of solutions from research to production, including reusable science components. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.
Applied Scientist II, Alexa International Team
US, WA, Bellevue
Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Set up experimentation frameworks for agile model analysis and A/B testing. * Collaborate with partner teams on LLM evaluation frameworks and post-training methodologies. * Contribute to end-to-end delivery of solutions from research to production, including reusable science components. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.
2026 Fall Quantum Applied Science Internship, Center for Quantum Computing
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers on a mission to develop a fault-tolerant quantum computer. Throughout your internship journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of Quantum Computing and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Quantum Research Science and Applied Science Internships in Santa Clara, CA and Pasadena, CA. We are particularly interested in candidates with expertise in any of the following areas: superconducting qubits, cavity/circuit QED, quantum optics, open quantum systems, superconductivity, electromagnetic simulations of superconducting circuits, microwave engineering, benchmarking, quantum error correction, fabrication, etc. Key job responsibilities In this role, you will work alongside global experts to develop and implement novel, scalable solutions that advance the state-of-the-art in the areas of quantum computing. You will tackle challenging, groundbreaking research problems, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
Senior Applied Scientist, Funnel Agentic Intel
US, WA, Seattle
Amazon Ads is building Ads Agent, an AI-powered agent that understands advertiser intent, reasons over campaign strategy, and executes across the full Amazon Ads portfolio. If you want to work at the frontier of agentic AI and large language models while directly impacting a multi-billion dollar business, this is your team. We are seeking an experienced Applied Scientist passionate about building intelligent agents that reason, plan, and act across complex advertising workflows. Ads Agent is an AI agent that simplifies how advertisers plan, launch, and optimize campaigns. Powered by AI, Ads Agent works alongside advertisers to automate time-consuming tasks, like identifying targeting segments, adjusting pacing across hundreds of campaigns, and generating SQL queries for advanced analytics. It also provides data-driven recommendations and simplifies analysis—all while providing transparency and control. With a broad mandate to experiment and innovate, we need applied scientists to define and build the future of advertising. Key job responsibilities - Design, build, and evaluate agentic systems that plan multi-step workflows, invoke tools, and take autonomous actions across Amazon Ads products on behalf of advertisers. - Define evaluation frameworks and benchmarks for agent reliability, correctness, safety, and advertiser satisfaction. - Analyze agent behavior through deep data analysis and rigorous A/B experimentation to identify failure modes, measure effectiveness, and derive business insights. - Partner with engineers, product managers, and UX designers to ship end-to-end agent experiences that are scalable, efficient, and reliable at Amazon scale. About the team We are a small, fast-moving team building a unified AI-native interface to all of Amazon Advertising. We sit at the intersection of large language models, agentic AI, and one of the world's most complex advertising ecosystems. If you want to shape how millions of advertisers interact with Amazon Ads, come build with us.
Senior Applied Scientist, Sponsored Products and Brands
US, WA, Seattle
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising! The Amazon Sponsored Products and Brands is looking for a talented Sr. Applied Scientist to join the Global Optimization science team at the forefront of advertising technology innovation. We are working backwards from emerging markets to reimagine Amazon's advertising stack from the ground up, leveraging multilingual and multi-modal GenAI technologies — including semantic hash designs, LLMs, and more — to deliver solutions that scale to non-US marketplaces from day one. This is your opportunity to be part of a small, high-impact team that prototypes, invents, and ships state-of-the-art solutions that will define the future of digital advertising. The ideal candidate combines entrepreneurial drive with deep technical expertise, thriving in ambiguous, fast-moving environments where you define the path forward with minimal structure. Our team regularly goes from ideas on the whiteboard to production-grade experiments. Your Customer Obsession fuels your passion for translating science into real-world value for millions of advertisers and customers worldwide. You are consistently Right, A Lot when navigating complex technical decisions, demonstrating the rare ability to identify solutions that drive maximum impact with minimal resources. Whether you're architecting scalable GenAI systems or optimizing multi-task recommendation engines, you cut through complexity to find the solutions that deliver the most results. Your GenAI experience goes beyond theoretical knowledge—you have successfully delivered value with state-of-the-art technologies at Amazon scale, understanding both the promise and practical challenges of deploying machine learning in production environments (evaluations, etc.). You're not just a scientist or just an engineer—you're a builder who sees the bigger picture and knows how to make it reality. Key job responsibilities * Architect next-generation systems that replace legacy monolithic infrastructure with scalable, intelligent solutions that scale worldwide on day one. * Pioneer breakthrough applied science in multi-modal GenAI applications for advertising, combining text, image, and multi-lingual support. * Drive end-to-end innovation from research ideation through production deployment at Amazon scale. * Lead cross-functional collaboration with product, engineering, and business teams to translate science into customer impact. About the team You will join a newly-founded team with a broad mandate to experiment and innovate, with a focus on driving growth of sponsored products ad experiences across non-US marketplaces. This broad charter gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers worldwide while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation.
Sr. Applied Scientist, Alexa Excellence AI Ops, Alexa Excellence AI Ops
IN, TN, Chennai
We are seeking a Senior Applied Scientist to join the Alexa Availability team within Alexa Excellence. This role leads the research and development of machine learning and statistical models that power Alexa's reliability at massive scale — serving hundreds of millions of customers globally. The ideal candidate will tackle complex, ambiguous problems spanning time series multivariate modeling, statistical anomaly detection, LLM-based operational intelligence, and adaptive threshold systems. They will design production-grade ML solutions, establish rigorous evaluation frameworks, and ensure AI systems are grounded, reliable, and free from systematic bias — leveraging techniques such as RAG, confidence scoring, knowledge graph integration, and counterfactual testing. This scientist will partner with engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability worldwide. They will drive the scientific agenda for the team, mentor fellow scientists, and influence the broader Alexa Excellence organization through technical leadership and cross-team collaboration. Key Focus Areas: Anomaly detection and predictive failure modeling Cross-service correlation and LLM-driven operational intelligence Production ML at the intersection of large-scale distributed systems and applied science Model reliability, hallucination mitigation, and grounding for operational AI Key job responsibilities As a Senior Applied Scientist on the Alexa Availability team, you will lead the research and development of machine learning and statistical models that power Alexa's reliability at scale. You will work on some of the most complex and ambiguous problems in the space — from time series multivariate modeling and statistical anomaly detection to LLM-based operational intelligence and adaptive threshold systems. A day in the life You will design and implement production-grade ML solutions, establish rigorous model evaluation frameworks, and ensure our LLM-powered systems are grounded, reliable, and free from systematic bias. You will apply techniques such as Retrieval-Augmented Generation (RAG), confidence scoring, knowledge graph integration, and counterfactual testing to ensure our AI systems make trustworthy operational decisions at scale. You will partner closely with software engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability for customers worldwide. You will drive the scientific agenda for your team, mentor fellow scientists, and influence the broader Alexa Excellence organization through your technical leadership and cross-team collaboration. About the team The Alexa Excellence team is at the heart of delivering a world-class Alexa experience to hundreds of millions of customers globally. Within Alexa Excellence, the Alexa Availability team is responsible for ensuring Alexa is always on, always responsive, and always reliable. We own the systems, signals, and science that detect, diagnose, and drive resolution of availability issues at scale — before customers ever notice. We are building the next generation of intelligent availability solutions powered by machine learning, large language models, and advanced statistical modeling. Our work spans anomaly detection, predictive failure modeling, cross-service correlation, and LLM-driven operational intelligence — all operating at the scale and reliability bar that Alexa demands. We operate at the intersection of large-scale distributed systems, applied machine learning, and operational excellence, and we are looking for scientists who can bring both deep technical rigor and a bias for production impact.
Language Data Scientist, Alexa International
US, WA, Bellevue
Amazon is seeking a Language Data Scientist to join the Alexa International science team as domain expert. This role focuses on expanding analysis and evaluation of conversational interaction data deliverables. The Language Data Scientist is an expert in conversation assessment processes, working closely with a team of skilled machine learning scientists and engineers, and is a key member in developing new conventions for relevant annotation workflows. The Language Data Scientist will be own unique data analysis and research requests that support the training and evaluation of LLMs and machine learning models, and the overall processing of a data collection. Key job responsibilities To be successful in this role, you must have a passion for data, efficiency, and accuracy. Specifically, you will: - Own data analyses for customer-facing features, including launch go/no-go metrics for new features and accuracy metrics for existing features - Handle unique data analysis requests from a range of stakeholders, including quantitative and qualitative analyses to elevate customer experience with speech interfaces - Lead and evaluate changing dialog evaluation conventions, test tooling developments, and pilot processes to support expansion to new data areas - Continuously evaluate workflow tools and processes and offer solutions to ensure they are efficient, high quality, and scalable - Provide expert support for a large and growing team of data analysts - Provide support for ongoing and new data collection efforts as a subject matter expert on conventions and use of the data - Conduct research studies to understand speech and customer-Alexa interactions - Collaborate with scientists and product managers, and other stakeholders in defining and validating customer experience metrics
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