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Principal Applied Scientist, AWS Marketing
US, WA, Seattle
Amazon Web Services (AWS) is building a world-class marketing organization that drives awareness and customer engagement with the goal of educating developers, IT and line-of-business professionals, startups, partners, and executive decision makers about AWS services and solutions, their benefits, and differentiation. As the central data and science organization in AWS Marketing, the Data: Science and Engineering (D:SE) team builds measurement products, AI/ML models for targeting, and self-service insights capabilities for AWS Marketing to drive better measurement and personalization, improve data access and analytical self-service, and empower strategic data-driven decisions. We work globally as a central team and establish standards, benchmarks, and best practices for use throughout AWS Marketing. We are looking for a Principal Applied Scientist with expertise in recommender engines, content ranking and rapid experimentation at scale, with strong interest in building scalable solutions in partnership with our engineering organization. You will lead strategic AI/ML and experimentation initiatives across AWS Marketing & Sales ranging anywhere between recommender engines, scaling experimentation and measurement science, real-time inference, and cross-channel orchestration. You are an hands-on innovator who can contribute to advancing Marketing AI/ML and experimentation technology in a B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will work with recognized B2B Marketing Science and AI/ML experts to develop large-scale, high-performing AI/ML models and rapid experimentation capabilities. We are at a pivotal moment in our organization where AI/ML, measurement and experimentation velocity has reached an unseen momentum, and we need to scale fast in order to maintain it. Your work will be a key input into a few of our S-Team goals. You will advance the state of the art in recommender engines, rapid experimentation at scale, and marketing science. Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. About the team We refuse to accept constraints, internal or external, and have a strong bias for action. We love data and believe that we can use it to deliver epic experiences for our millions of prospect customers. We work across all areas of AWS Marketing including core marketing data solutions, insights and reporting, targeting and personalization, measurement, and the operational systems to support each of these areas. As a multi-functional team of experts, we deliver scaled solutions that are used globally across AWS Marketing. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA | Vancouver, WA, USA
Flight Dynamics Engineer , Project Kuiper
US, WA, Redmond
Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. We are searching for Flight Dynamics Engineer who demonstrable skills in supporting the following areas in Flight Dynamics: Mission Design of LEO Constellations, Maneuver Planning, Navigation, Fleet Operations, and Flight Dynamics System development. This position requires experience in simulation and analysis of astrodynamics models and spaceflight trajectories. Experience in mission operations of multiple small satellites and fault mode analysis is highly desired. Working with the Kuiper engineering team, you will: • Implement high fidelity modeling techniques for analysis and simulation of large constellation concepts. • Help develop algorithms for station-keeping and constellation maintenance. • Perform analysis in support of multi-disciplinary trades within the Kuiper team. • Help develop the Kuiper ground system’s Flight Dynamics System functional requirements, including navigation, maneuver planning, maneuver reconstruction and trending. • Work closely with GNC engineers to manage on-orbit performance and develop flight dynamics operations processes. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. We are open to hiring candidates to work out of one of the following locations: Redmond, WA, USA
2024 Applied Science Intern (NSW, VIC, SA, QLD, ACT)
AU, NSW, Sydney
Are you excited about understanding the 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? A research internship at Amazon is an opportunity to work with leading machine learning researchers on incomparable datasets using the best tools and hardware in the world. It is an opportunity for PhD students and recent PhD graduates in Computer Vision, Deep Learning, Natural Language Processing, and broader Machine Learning to address challenges at a scale that is impossible elsewhere. 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 impact. As an Applied Scientist Intern, you will be working in the closet Amazon offices to you (Sydney, Melbourne, Canberra, Adelaide, Brisbane) in a fast-paced, cross-disciplinary team of researchers who are pioneers in the field. You will take on complex problems, and work on 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. Key job responsibilities Are you excited about using state-of-the-art Deep Learning, Computer Vision, Natural Language Processing algorithms and large data sets to solve real world problems? A research internship at Amazon is an opportunity to work with leading machine learning researchers on exciting problems using the best tools and hardware in the world. It is an opportunity for PhD students and recent PhD graduates in Computer Vision, Deep Learning, Natural Language Processing, and broader Machine Learning to address challenges at a scale that is impossible elsewhere. 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 impact. As an Applied Scientist Intern, you will be working in a fast-paced, cross-disciplinary team of researchers who are pioneers in the field. You will take on complex problems, and work on 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 building prototypes, you may even deliver these to production in customer facing applications. We are open to hiring candidates to work out of one of the following locations: Adelaide, SA, AUS | Brisbane, QLD, AUS | Canberra, ACT, AUS | Melbourne, VIC, AUS | Perth, WA, AUS | Sydney, NSW, AUS
Applied Scientist II, Search Science and AI
US, CA, Palo Alto
The Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. Amazon’s large scale brings with it unique problems to solve in designing, testing, and deploying relevance models. We are seeking a strong applied Scientist to join the Experimentation Infrastructure and Methods team. This team’s charter is to innovate and evaluate ranking at Amazon Search. In practice, we aim to create infrastructure and metrics, enable new experimental methods, and do proof-of-concept experiments, that enable Search Relevance teams to introduce new features faster, reduce the cost of experimentation, and deliver faster against Search goals. Key job responsibilities You will build search ranking systems and evaluation framework that extend to Amazon scale -- thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. As a Senior Applied Scientist you will find the next set of big improvements to ranking evaluation, get your hands dirty by building models to help understand complexities of customer behavior, and mentor junior engineers and scientists. In addition to typical topics in ranking, we are particularly interested in evaluation, feature selection, explainability. A day in the life Our primary focus is improving search ranking systems. On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and guiding teams on best practices. You will also find yourself in meetings with business and tech leaders at Amazon communicating your next big initiative. About the team We are a team consisting of software engineers and applied scientists. Our interests and activities span machine learning for better ranking, experimentation, statistics for better decision making, and infrastructure to make it all happen efficiently at scale. We are open to hiring candidates to work out of one of the following locations: Palo Alto, CA, USA
Applied Scientist, SDO Privacy - PDC team
RO, Bucharest
Amazon’s mission is to be earth’s most customer-centric company and our team is the guardian of our customer’s privacy. Amazon SDO Privacy engineering operates in Austin – TX, US and Iasi, Bucharest – Romania. Our mission is to develop services which will enable every Amazon service operating with personal data to satisfy the privacy rights of Amazon customers. We are working backwards from the customers and world-wide privacy regulations, think long term, and propose solutions which will assure Amazon Privacy compliance. Our external customers are world-wide customers of Amazon Retail Website, Amazon B2B services (e.g. Seller central, App / Skill Developers), and Amazon Subsidiaries. Our internal customers are services within Amazon who operate with personal data, Legal Representatives, and Customer Service Agents. You can opt-in for being part of one of the existing or newly formed engineering teams who will contribute to Amazon mission to meet external customers’ privacy rights: Personal Data Classification, The Right to be forgotten, The right of access, or Digital Markets Act – The Right of Portability. The ideal candidate has a great passion for data and an insatiable desire to learn and innovate. A commitment to team work, hustle and strong communication skills (to both business and technical partners) are absolute requirements. Creating reliable, scalable, and high-performance products requires a sound understanding of the fundamentals of Computer Science and practical experience building large-scale distributed systems. Your solutions will apply to all of Amazon’s consumer and digital businesses including but not limited to Amazon.com, Alexa, Kindle, Amazon Go, Prime Video and more. Key job responsibilities As an applied scientist on our team, you will apply the appropriate technologies and best practices to autonomously solve difficult problems. You'll contribute to the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. You will collaborate with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. Your work will directly impact the trust customers place in Amazon Privacy, globally. We are open to hiring candidates to work out of one of the following locations: Bucharest, ROU
Senior Applied Scientist, EU ATS Science and Tech
DE, BE, Berlin
Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer’s doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! Amazon Transportation Services is seeking Applied (or Research) Scientists. As a key member of the central Research Science Team of ATS operations, these persons will be responsible for designing algorithmic solutions based on data and mathematics for optimizing the middle-mile Amazon transportation network. The job is opened in Luxembourg, Barcelona, Berlin or London, designed to maximize interaction with the team and stakeholders, but we will consider applicants with remote work requirements as well. Key job responsibilities Solve complex optimization and machine learning problems using scalable algorithmic techniques. Design and develop efficient research prototypes that address real-world problems in the middle-mile operations of Amazon. Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making. Communicate to leadership results from business analysis, strategies and tactics. A day in the life You will be brainstorming algorithmic approaches with team-mates to solve challenging problems for the middle-mile operations of Amazon. You will be developing and testing prototype solutions with above algorithmic techniques. You will be scavenging information from the sea of Amazon data to improve these solutions. You will be meeting with other scientists, engineers, stakeholders and customers to enhance the solutions and get them adopted. About the team The Science and Tech team of ATS EU is looking for candidates who are looking to impact the world with their mathematical and data-driven skills. ATS stands for Amazon Transportation Service, we are the middle-mile planners: we carry the packages from the warehouses to the cities in a limited amount of time to enable the “Amazon experience”. As the core research team, we grow with ATS business to support decision making in an increasingly complex ecosystem of a data-driven supply chain and e-commerce giant. We schedule more than 1 million trucks with Amazon shipments annually; our algorithms are key to reducing CO2 emissions, protecting sites from being overwhelmed during peak days, and ensuring a smile on Amazon’s customer lips. Our mathematical algorithms provide confidence in leadership to invest in programs of several hundreds millions euros every year. Above all, we are having fun solving real-world problems, in real-world speed, while failing & learning along the way. We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making. We like to learn new techniques to surprise business stakeholders by making possible what they cannot anticipate. For this reason, we work closely with Amazon scholars and experts from Academic institutions. We code our prototypes to be production-ready We prefer provably optimal solutions than heuristics, though we settle for heuristics when performance dictates it. Overall, we appreciate the value of correct modeling. We are open to hiring candidates to work out of one of the following locations: Berlin, BE, DEU
Sr Manager, Research Science, Amazon Health
US, WA, Seattle
Do you wish to create the greatest possible worldwide impact in healthcare? We, at Amazon Health Store Tech, are working towards the best-in-class healthcare storefront to make high-quality healthcare reliable, accessible, and intuitive. Our mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. We are looking to hire and develop subject-matter experts in AI who focus on data analytics, machine learning (ML), natural language understanding (NLP), and deep learning for healthcare. We target high-impact algorithmic unlocks in areas such as natural language understanding (NLU), Foundation Models, Large Language Models (LLMs), document understanding, and knowledge representation systems—all of which are of high-value to our healthcare products and services. If you are a seasoned, hands-on Applied Science Director with a track record of delivering to timelines with high quality, deeply technical and innovative, we want to talk to you. You will bring AI and machine learning advancements to real-time analytics for customer-facing solutions in healthcare. You will explore, innovate, and deliver advanced ML-based technologies that involve clinical and medical data. You are a domain expert in one or more of the following areas: natural language processing and understanding (language models, transformers like BERT, GPT-3, T-5, etc.), Foundation Models and LLMs, deep learning, active learning, reinforcement learning, and bioinformatics. Key job responsibilities As an Applied Science Manager, you will take on challenging and ambiguous customer problems, distill customer requirements, and then deliver solutions that either leverage existing academic and medical research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to its implementation. A successful candidate has excellent technical depth, scientific vision, great implementation skills, and a drive to achieve results in a collaborative team environment. You should enjoy the process of solving real-world, open-ended problems that, quite frankly, haven’t been solved at scale anywhere before. Along the way, we guarantee you’ll get opportunities to be a fearless disruptor, prolific innovator, and a reputed problem solver—someone who truly enables machine learning and statistics to truly impact the lives and health of millions of customers. You will build and grow this team of Applied Scientists and guide this top talent to push the boundary of Science and next generation of product. They will lead the technical implementation of our evidence-based retrieval sub-system that ingests, indexes and retrieves relevant data in different forms and from multiple sources given the customer question and context. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Data Science Manager, Workforce Intelligence
US, VA, Arlington
Funnel Science and Analytics team is looking for a Data Science Manager. This individual will be responsible for leading a team of scientists to own and accelerate science and analytics to predict actions for mitigating operational risk, building tools to perform scenario planning, improving candidate experience, and collaborating with other science teams to achieve cost effectiveness. Key job responsibilities As a Data Science Manager (DSM), you will lead a team of scientists to design studies and experiments, leverage data science workflows, build predictive models, conduct simulations, create visualizations, and influence science and analytics practice across the organization. Identify useful research avenues for increasing candidate conversion, test, and create well written documents to communicate to technical and non-technical audiences. About the team Funnel Science and Analytics team finds ways to maximize the conversion and early retention of every candidate who wants to be an Amazon Associate. By focusing on our candidates, we improve candidate and business outcomes, and Amazon takes a step closer to being Earth’s Best Employer. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA
Senior Data Scientist, Search Customer Experience Data Science and Analytics
US, WA, Seattle
Amazon is one of the most popular sites in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. Our team leads the data science and analytics efforts for the Search Customer Experience (Search CX) and we own multiple aspects of understanding how we can understand and measure customer satisfaction with our experiences. This include building science based insights and reporting pipelines to define and track customer focused metrics. We are diving deep in our CXs and looking to derive insights to inform product roadmaps using machine learning, experimentation and causal inference. Key job responsibilities We are looking for an experienced and curious data scientist with superior analytical skills to inform the data science charter of the Data Science and Analytics team. This position is critical in helping us learn more about our data and find opportunities to delight customers with data driven insights and machine learning models. The Data Science and Analytics team owns data science, data engineering and business intelligence. You will be supporting multiple business and technical stakeholders with high velocity analytics. This role is uniquely positioned in the team as we have a growing need for looking around corners, prioritize opportunities using data driven insights and solution these opportunities using different AI techniques and causal inference models. You will be diving deep in our data and have a strong bias for action to quickly produce high quality data analyses with clear findings and recommendations. As part of our journey to learn about our data, some opportunities may be a dead end and you will balancing unknowns with delivering results for our customers. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Applied Science Manager, Seller Growth and Insights
US, WA, Seattle
Join us in the evolution of Amazon’s Seller business! The Selling Partner Recruitment and Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential by using our scaled, automated, and self-service tools. We aim to provide intelligent insights that are granular and actionable to help Sellers launch new products and engage with customers. To achieve that, we leverage the deep structured and unstructured data to create science-based insights about their business and surface insights and recommend actions to Sellers via our products, such as Amazon Brand Analytics (ABA) and Opportunity Explorer (OX). We are looking for a talented and passionate Applied Science Manager to manage our growing team of Applied Scientists and Data Scientists to build world class statistical and machine learning models, working closely with PM, UX, engineering, Seller Growth Consulting teams to provide actionable insights to improve SPs' business. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. As a leader, you will lead and work with scientists to understand seller business, identify opportunities, extract insights and solve the problems using data-driven algorithms and bring the solutions to seller-facing products. You should be willing to dive deep when needed, move rapidly with a bias for action, and get things done. You should have an entrepreneurial spirit, love autonomy, know how to build and deliver pioneering solutions to challenging problems. This role will demand resourcefulness and a fearless willingness to learn on both the technical and business side. Key job responsibilities (1) Lead a team of scientists in identifying opportunities for Sellers and building scalable machine learning solutions. (2) Define a long-term science vision, driven from our sellers’ needs, translating that direction into science roadmaps, and foster cross-team collaboration to execute complex projects. (3) Own science team roadmap, balance multiple projects efficiently and achieve goals in a fast-paced, dynamic environment. (4) Collaborate effectively with program/product managers, and business leadership to deliver science-based seller facing products. (5) Grow and manage a science team, actively mentoring, developing, and promoting team members. (6) Act as a technical supervisor, able to assess scientific direction, technical design documents, and steer development efforts to maximize project delivery. A day in the life We are open to hiring candidates to work out of one of the following locations: New York, NY, USA | Seattle, WA, USA
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