ARA Program Rules

Last updated: March 26, 2025

By applying to or participating in the Amazon Research Awards Program (the “ARA Program”), you (defined below) agree to the following rules (“Rules”). These Rules are solely between Amazon.com, Inc. and its affiliates (“Amazon”, “we”, “us”, or “our”) and the entity that you represent (“you” or “your”), including the lead researcher/s who applies to the ARA Program (the “Principal Investigator”) and any members of the research team. Capitalized terms not defined herein may be defined in the AWS Agreements (as defined below). You and/or the Principal Investigator are responsible for distributing these Rules to all members of the research team before they participate in any research in connection with a proposal funded by the ARA Program.

I. Eligibility Requirements

To be eligible for an ARA Program award (“Award”), the Principal Investigator must be (1) either a full-time faculty member at an accredited academic institution or a permanent researcher at a non-governmental organization with recognized legal status in its country (equivalent to 501(c)(3) status under the United States Internal Revenue Code) and (2) at or above the age of majority in their jurisdiction of residence at the time of application. Each Principal Investigator is permitted to submit only one proposal to the ARA Program per call for proposal period.

By submitting your proposal to the ARA Program, you represent that your Principal Investigator:

(a) is not a paid employee of a government entity (other than an accredited academic institution);

(b) is not under US export controls or sanctions;

(c) has not been a director, officer, employee, intern or contractor of Amazon within the 12 months preceding submission of your proposal to the ARA Program (“Ineligible Personnel”);

(d) is not a member of the immediate family or household of Ineligible Personnel; and

(e) has not participated in or had decision-making authority over any cloud infrastructure procurements involving Amazon.

The ARA Program is void in Cuba, Iran, Syria, North Korea and the Crimea, Luhansk and Donetsk regions of Ukraine, and where otherwise prohibited by law.

Amazon employees, including employees of Amazon Web Services, Inc. (“AWS”), are not eligible to receive an Award.

Amazon is not responsible for your internal organizational policies and procedures that may restrict your (including the Principal Investigator’s) ability to submit a proposal to the ARA Program.

II. Application Content

No proposal to the ARA Program may contain any confidential information and no part may be marked as ‘confidential.’ Amazon does not accept any legal obligation (whether of confidentiality, compensation, return or otherwise) with respect to any proposals. Amazon reserves the right to implement competitive, similar, or identical ideas in the future, without restriction or obligation. You understand and acknowledge that Amazon has wide access to technology, designs, and other materials, and may work on and/or develop projects and ideas that may be competitive with, similar to, or identical to your proposal in theme, idea, format or other respects, inclusive. You acknowledge and agree that you will not be entitled to any compensation as a result of Amazon’s use of any such similar or identical material that has or may come to Amazon from other sources.

You represent and warrant that your proposal:

(a) is either your original work or an update to your original work;

(b) does not, to your knowledge, infringe any third-party patent rights; and

(c) does not, to your knowledge, infringe, misappropriate or otherwise violate any other third-party intellectual property rights (i.e., other than patent rights), including any copyrights, trade secrets, trademarks, contract or licensing rights, rights of publicity or privacy, or moral rights.

III. Awards

Proposals selected for funding will receive an Award that may include cash, Promotional Credit (as defined in the AWS Promotional Credit Terms & Conditions), or both. Award funding is not extendable or transferable without our written consent, but you may submit new proposals for subsequent ARA Program calls.

All Award amounts will be determined by Amazon in its sole discretion. Any cash component of an Award:

(a) will be structured as a one-time unrestricted gift to your Principal Investigator’s academic institution or organization;

(b) will be provided directly to your academic institution or organization for distribution and management; and

(c) may not be used for indirect expenses which are not allocable, reasonable, adequately documented, and consistent with established policies and practices of your academic institution or organization.

You are responsible for the administration and apportionment of any costs and expenses associated with an Award, including any allowable and allocable overhead or indirect costs. In order to process any cash Award, you will be required to complete administrative requirements, which may include submitting a W-9 form to us, completing a tax questionnaire, and registering in Amazon’s Payee Central System. If you do not fulfill the administrative requirements for processing cash Awards within two years of your receipt of an Award notification, Amazon reserves the right to withhold payment. Any payment from Amazon to you under the Award may be issued by a purchase order. Except where prohibited by law, you are responsible for all taxes (including income tax and value added tax) that may be imposed on you by relevant local tax authorities.

These Rules, the agreements referenced herein, and any other agreement regarding the relationship between you and Amazon will constitute a Master Agreement under the terms of the purchase order.

IV. AWS Customer Agreement and AWS Promotional Credit Terms & Conditions

Amazon may make available to you an amount of AWS promotional computing credits (“AWS Credits”) for use in support of this Agreement. AWS Credits provided to University under this Agreement are subject to the AWS Promotional Credit Terms and Conditions (as may be updated from time to time on the AWS website). You acknowledge and agree that any use of AWS services, including but not limited to use of AWS Credits, is subject to the terms and conditions set forth in the AWS Customer Agreement (https://aws.amazon.com/agreement/), and/or any separate, bespoke agreement that you have entered into with Amazon governing use of AWS services (collectively, the “AWS Agreements”). In the event of any conflict between this Agreement and the AWS Agreements, the terms of the AWS Agreements shall take precedence.

V. Privacy

You acknowledge and agree that we may collect, store, share, and otherwise use personally identifiable information provided during the ARA Program application process, including but not limited to, name, mailing address, phone number, and email address. All personally identifiable information collected is subject to, and will be used in accordance with, the Amazon Privacy Notice, including for administering the ARA Program and verifying applicants’ identities, addresses, and telephone numbers in the event a proposal is selected for funding. By participating in the ARA Program, you consent to the transfer of personal data to the United States for purposes of administering the ARA Program, conducting publicity about the ARA Program, and additional purposes that are consistent with goals relating to the ARA Program. The data controller for information collected by us is Amazon.com, Inc., 410 Terry Ave North, Seattle, Washington 98109, USA.

VI. Publicity

Except where prohibited, you consent to our use of your name and the Principal Investigator’s name and title, proposal title, and proposal abstract text for purposes of identifying Amazon’s support of you, the Principal Investigator, the proposal and/or the ARA Program.

You may acknowledge our support by stating that your research is supported by the ARA Program (e.g., “Research reported in this [publication/press release] was supported by an Amazon Research Award, [Cycle /Year].”). Any use of Amazon or AWS logos is subject to the Amazon Trademark Guidelines and AWS Trademark Guidelines, respectively. Any other use of Amazon or AWS logos requires Amazon’s or such affiliate’s prior written consent. You must receive Amazon’s prior written consent before issuing a press release or making any public disclosure regarding your participation in the ARA Program. You agree not to misrepresent or embellish the relationship between us and you. You will not imply any relationship or affiliation between us and you except as expressly permitted by these Rules.

VII. Limitation of Liability

TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU ACCEPT THE CONDITIONS STATED IN THESE RULES, AGREE TO BE BOUND BY THE DECISIONS OF AMAZON, AND WARRANT THAT YOU ARE ELIGIBLE TO PARTICIPATE IN THE ARA PROGRAM. TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU, EACH RESEARCH TEAM MEMBER, THE PRINCIPAL INVESTIGATOR AND THE PRINCIPAL INVESTIGATOR’S INSTITUTION HEREBY RELEASES AMAZON FROM, AND WAIVES ANY AND ALL CLAIMS AGAINST AMAZON FOR, ANY LOSSES, LIABILITY, AND DAMAGES OF ANY KIND, (INCLUDING FOR ANY LOSS OF DATA, LOST PROFITS, COST OF COVER OR OTHER SPECIAL, INCIDENTAL, CONSEQUENTIAL, INDIRECT, PUNITIVE, EXEMPLARY OR RELIANCE DAMAGES) INCURRED OR SUSTAINED IN CONNECTION WITH OR ARISING OUT OF (1) THE ARA PROGRAM OR ANY TRAVEL OR ACTIVITY RELATED THERETO, (2) USE OF ANY PROPOSAL OR RIGHTS THEREIN, OR (3) ANY BREACH OF ANY AGREEMENT OR WARRANTY ASSOCIATED WITH THE ARA PROGRAM, INCLUDING THESE RULES, HOWEVER CAUSED AND REGARDLESS OF THEORY OF LIABILITY.

VIII. Changes

We may amend any of these Rules at our sole discretion by posting the revised terms on the ARA Program website. Your continued participation in the ARA Program after the effective date of the revised Rules constitutes your acceptance of the rules.

IX. Disputes

Any dispute or claim relating in any way to the ARA Program will be resolved in accordance with terms set forth in the AWS Agreements.

X. Representations and Warranties

You represent and warrant that:

(a) your receipt of any Award is neither prohibited by nor inconsistent with any applicable laws, regulations, or binding orders, including applicable ethics rules or internal institutional rules;

(b) you have completed or will complete all legal and ethical requirements necessary to accept the Award;

(c) your receipt of the Award will not knowingly create a conflict of interest for Amazon;

(d) the Principal Investigator has not participated in, nor had, and do not anticipate participating in or having, any decision-making authority over, any procurements or purchasing decisions involving Amazon on behalf of your organization during the previous or upcoming twelve (12) months; and

(e) you will properly book and record the Award in your accounting documents in accordance with applicable laws and regulations.

In the event that your representations and warranties under this section are or become inaccurate, you must notify us immediately (research-awards@amazon.com) and any Award your organization receives will be voidable.

US, CA, Sunnyvale
We are seeking an Applied Scientist II to work on development of an AI-based data intelligence and classification platform that will redefine how security and privacy assessments and enforcement are conducted at scale. This mission-critical platform will leverage AI-driven autonomous agents to conduct proactive, intelligent security operations across the company. The platform will integrate deeply with internal security, privacy, engineering, and cloud-native tools to provide self-serve, automated insights, verifications, and enforcement mechanisms. This role requires strong technical expertise in AI/ML, LLMs, and distributed cloud infrastructure, as well as thought leadership to drive alignment across multiple teams, customers, and business units. This is an opportunity to shape the future of AI-driven security and privacy assurance at an enterprise scale, defining standards, influencing company-wide security posture, and leading technical innovation at the highest level. Key job responsibilities * Architect and define the next-generation data classification and search matching platform, leading the technical strategy for AI-driven security automation across applied science and engineering teams * Build on multi-agent LLM framework, and influence your organizations in adopting the promising approaches * Develop a highly scalable, traditional ML-based as well as LLM-based intelligent security agent framework that enables internal teams to automate processing of structured and unstructured data * Combine depth and breadth of domain expertise and provide technical leadership to the entire team while also doing hands-on work by diving deep into details to diagnose complex system performance problems. About the team The Data Categorization team helps Amazonians understand their data and govern it at scale and ensures experiences delivered by Amazon to our customers uphold our high security and privacy standards. The science team harnesses AI to strengthen Amazon’s privacy and security posture more efficiently and effectively.
GB, London
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
US, CA, Sunnyvale
Are you excited about developing state-of-the-art Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms and designs using large data sets to solve real world problems? Do you have proven analytical capabilities and can multi-task and thrive in a fast-paced environment? Do you want to build a foundation for your career after your Master's or Ph.D program at an industry-leading company? You enjoy the prospect of solving real-world problems that, quite frankly, have not been solved at scale anywhere before. Along the way, you’ll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver—someone who truly enables machine learning to create significant impacts. As an Applied Scientist, you will bring statistical modeling and machine learning advancements to data analytics for customer-facing solutions in complex industrial settings. You will be working in a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products
US, WA, Seattle
We are seeking a senior Applied Scientist to join a science team within Amazon Customer Service that is reimagining how customers are connected with the right support experience. This is a senior technical leadership role where you will drive scientific strategy, mentor junior scientists, and deliver foundational models that power real-time personalization at scale. Key job responsibilities - Lead the science for understanding the demand side of customer service interactions - Characterize who is contacting us, what they need, and how complex their situation is - Invent novel representation learning approaches that encode customer interactions - Directly inform intelligent routing decisions across hundreds of millions of annual contacts
US, WA, Seattle
We are seeking an Applied Scientist to join a science team within Amazon Customer Service that is reimagining how customers are connected with the right support experience. This is a role at the intersection of representation learning, behavioral modeling, and large-scale experimentation where you will see your science deployed in production systems serving real-time decisions. Key job responsibilities - Develop machine learning models that capture how service associates perform across different problem types and how their capabilities evolve over time - Power intelligent routing decisions across hundreds of millions of annual customer contacts - Directly improve both customer experience and associate satisfaction through model-driven decisions - Work at the intersection of representation learning, behavioral modeling, and large-scale experimentation - Deploy science into production systems serving real-time decisions
US, CA, Sunnyvale
Amazon's PRISM team is seeking an innovative Applied Scientist to build the intelligence layer powering the Catalog Diagnostic Assistant — a conversational AI agent that unifies Amazon's fragmented catalog diagnostic experience into a single natural-language interface. Rather than switching between legacy tools, internal users ask CDA a question in plain language and CDA coordinates across data sources, reasons through complex diagnostic workflows, and returns a combined answer with source citations. This role sits at the intersection of Generative AI, agentic architectures, and large-scale information retrieval applied to the world's largest product catalog. You will design and build the scientific core of an agent that autonomously investigates catalog anomalies — diagnosing why products aren't live, why attributes aren't publishing, or why matching decisions went wrong — across billions of products, petabytes of multimodal data, and dozens of marketplaces. You will be the founding scientist for the CDA product, defining the research agenda for agentic diagnostics, developing novel approaches to skill-based reasoning and tool orchestration, and owning the full lifecycle from problem formulation through production deployment at Amazon scale. You will pioneer advanced GenAI solutions that power next-generation agentic experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog and tackle problems at the frontier of AI research. Key job responsibilities - Formulate open research problems at the intersection of GenAI, agentic reasoning, and large-scale catalog diagnostics — defining how an autonomous agent should decompose, investigate, and explain complex catalog issues - Design and develop novel agentic architectures (skill planning, tool selection, multi-step reasoning, chain-of-thought verification) that enable CDA to autonomously resolve diagnostic workflows that traditionally required manual expert investigation - Build and optimize retrieval-augmented generation (RAG) systems over Amazon's catalog data, ensuring the agent retrieves the right evidence from the right data sources to ground its diagnostic answers - Advance the science of efficient model deployment — developing distillation, compression, and LLM serving optimization strategies that preserve diagnostic reasoning quality in production-grade architectures while reducing latency and cost - Make frontier models reliable for autonomous decisions — advancing uncertainty calibration, confidence estimation, and interpretability methods so CDA's agentic diagnoses can be trusted at scale - Own the full research lifecycle from problem formulation through production deployment — designing rigorous experiments, iterating rapidly, and seeing your research directly improve diagnostic accuracy and coverage - Partner closely with CDA engineers to translate research prototypes into production systems serving thousands of daily diagnostic sessions - Shape the team's research vision by defining technical roadmaps that balance foundational scientific inquiry with measurable product impact - Mentor engineers on advanced ML/GenAI techniques, experimental design, and scientific rigor About the team We are a GenAI science team within Amazon's Selection and Catalog Systems (ASCS) organization. Our mission is to advance state-of-the-art Generative AI to deeply understand, uniquely identify, and intelligently diagnose every product at Amazon scale. We push the boundaries of multimodal LLMs, agentic systems, and generative AI to solve foundational catalog challenges — from product identity and semantic matching to automated catalog diagnostics and intelligent catalog analytics. Our scientists work across multiple high-impact problem spaces: establishing canonical product identity across billions of items, powering next-generation agentic experiences for catalog operations, and building AI systems that make Amazon's catalog self-diagnosing and self-healing. We operate at the frontier of AI research applied at unprecedented scale — petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity. This is a collaborative, fast-moving environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your ideas at scale, and publish your findings at top venues.
US, CA, San Francisco
We are seeking a Member of Technical Staff — Mechanical Engineer to lead the structural and electromechanical design of advanced high degree-of-freedom robotic systems within a frontier AI and robotics research lab. You will own the mechanical architecture of our robotics platform end-to-end: actuator selection, joint design, thermal management, cable routing, sensing integration, and structural optimization — all under the demanding constraints of a high-DoF system that must be lightweight, robust, and production-viable. This is a unique opportunity to define the physical design direction of a next-generation robotics platform from first principles. The ideal candidate has deep experience designing complex robotic systems and scaling hardware from concept through prototyping to production. You thrive on analytical problem solving, possess strong intuition for structural and electromechanical tradeoffs, and are equally comfortable in CAD and on the shop floor. You will be the technical lead of a small team of talented mechanical engineers while collaborating closely with electrical, firmware, controls, and AI research teams to set the mechanical and structural direction of the platform. Beyond core platform development, this role offers real latitude to push into novel territory — novel actuation methods, advanced sensor integration, or new approaches to mechatronic packaging. If you have research instincts alongside shipping discipline, you'll find an environment that rewards both. We're looking for someone who wants to be the technical authority on how a high-performance robot is physically built, not just a contributor to the effort. 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. - Drive rapid iteration and prototyping cycles — from concept sketches through functional hardware — to accelerate learning and compress development timelines in a fast-paced R&D environment. - Partner with the AI research team to establish simulation pipelines that enable rapid exploration of mechanical design space, informing actuator choices, structural topology, and system-level tradeoffs before committing to physical builds. - 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.
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
IN, KA, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and visual), supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, product similarity, using GenAI, LLMs, NLP and Computer Vision. Key job responsibilities As an Applied Science Manager, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will Lead scientists on the team and oversee research and development projects at various stages ranging from initial exploration to deployment into production systems. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will create the environment in the team to file for patents and/or publish research work where opportunities arise. You will impact the large product strategy, identifies new business opportunities and provides strategic direction to the team.
US, VA, Arlington
The AWS Certification team is seeking a Psychometrician with experience working with criterion-referenced assessment programs to support a large global AWS Certification and Credentialing program. In this role, you will support all psychometric aspects of exam development and operation, including job analyses, standard setting, automated test assembly, item and test analyses, optimal item bank design, quality assurance, and project planning. You will work closely with a team of psychometricians, subject matter experts, certification exam program managers, publishing, delivery, security, and product management teams to support ongoing analyses of exam and credential data. To be successful in this position, you must be highly motivated, creative, detail oriented, and a self-starter who is able to think big, execute, ensure high quality, yet stay focused on the details. Key job responsibilities • Conduct Job Task Analysis (JTA) workshops and post-JTA survey analyses to define the blueprint and test specifications for new certifications or updates to existing certifications • Conduct standard setting studies to set the passing score for exams and credentials • Run item analysis to evaluate quality and performance of exam items • Use automated test assembly procedures to assemble forms or item pools • Work with content development to track item bank trends and optimize the health of item banks • Support the development of a cloud-based analytics and reporting system • Partake in development and performance analysis of credentials • Interpret and clearly communicate the results of analyses to stakeholders through written and oral reports • Follow the accreditation standards set by ISO/IEC:2012 17024 and the National Council for Certifying Agencies (NCCA) as they relate to valid psychometric practices • Contribute to the development and execution of the strategic goals regarding the AWS certification and credentialing program. • Consult with leadership, internal staff, external consultants, and industry leaders regarding advancement of current offerings