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Location: Princeton, NJ, USA
Faculty advisor: Sanjeev Arora

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We're an eclectic team of research-oriented undergraduate and graduate students in Princeton's CS and math departments.

By Princeton University
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Individually, our specialties span a wide gamut, from machine learning theory to computer vision to distributed systems. We're united by a passion for the multifaceted field of artificial intelligence, and a vision of bringing change and surprise to the world through our research. Using a combination of tried-and- true techniques in natural language processing and freshly minted methods in deep learning, we hope to bring to you a socialbot that will understand and react to the social context, providing endless interesting and empathetic conversation.

Niranjani P. - Team leader

I'm a second year PhD student in Computer Science, advised by Professor Barbara Engelhardt. In 2013, I graduated from the University of Cambridge in Information and Computer Engineering (BA, MEng). Following that, I was with a start-up for two years, working on the research and development of speech recognition software. My current research interests are primarily in machine learning methods motivated by clinical medicine, spanning reinforcement learning, time series modelling, natural language processing and knowledge representation.

Alex B.

I'm a second year CS PhD student advised by Han Liu working on statistical learning and deep learning. At Princeton, I've worked on robustness of machine learners to attack (paper accepted at NIPS) and online hyperparameter optimization for deep networks. I also did a research internship at Google working on transfer learning for speech recognition with deep recurrent networks. Before Princeton I worked at Wynyard on stochastic process models of crime and distributed network security software for Apache Spark. My undergraduate research was on signal processing algorithms for ventilator management in the intensive care unit.

Ari S.

I'm a second year Computer Science PhD student working with Han Liu. I am interested in both general machine learning methodologies and applications in computer vision, robotics, and natural language processing. I am supported by an NDSEG Fellowship. Before Princeton I completed a research fellowship at the National Institutes of Health, focusing on computer-aided diagnostics. I developed software for automated detection of pathologies (e.g., enlarged lymph nodes, tumors) on CT and MRI images. Prior to NIH, I studied mathematics as an undergraduate at the University of Florida.

Cyril Z.

I'm a PhD student in Computer Science, studying algorithms and machine learning theory. I received my B.S. in Computer Science from Yale University, where I worked on fast Laplacian solvers, exoplanet physics, and various artsy things. I dream of uniting the beauty and rigor of theoretical computer science with the humanism and pragmatism of its applications.

Daniel S.

Daniel is a second-year graduate student working at the intersection of artificial intelligence and distributed systems. After receiving his bachelor's in Computer Science from Harvard, he spent five years in industry working on three-dimensional computer vision, constructing laser scanners with high dynamic range, and cluster computing on three-dimensional data. In the last year, he has built a robot that autonomously scans large indoor spaces in real time powered with a distributed computing back end. He was also on the MIT-Princeton team that took 3rd place at the 2016 Amazon Picking Challenge (top non-industry entrant). He currently works on deadline computing.

Davit B.

I graduated UCL majoring in Computer Science supervised by Prof. Lourdes Agapito. I developed Cyclop War during New Year's night. Launched multi-platform casual game Froo Zoo played by 100K users at age 17. At 18 I was featured by TechCrunch and started Newsly. At 19 I founded Cyclop. I am inspired by Elon Musk, Steve Jobs, DeepMind and the possible applications of Recurrent Neural Networks in vision. I am also co-founder Castly.tv, which is a video on demand platform that lets users sync-watch movies with friends and family. Started my PhD at 20.

Holden L.

I am a third-year PhD student advised by Sanjeev Arora. My research is on provable algorithms for machine learning, including areas such as neural networks, natural language processing, and reinforcement learning. I graduated with at B.Sc. in Mathematics from MIT in 2013 and M.A.St. in Mathematics from the University of Cambridge in 2014. My other interests include creative writing, teaching, science fiction, and rationality.

Jason G.

I majored in applied math and computer science in USTC between 2010 and 2014 and joined the Statistical Machine Learning (SMiLe) lab at Princeton in Sept. 2014 for graduate study under the supervision of Prof. Han Liu. I worked on CUDA programming for real time rendering algorithm in USTC. In the summer of 2013, I developed a set of computer vision toolkits for microscopy video archive processing while working as a research intern at the Oxford Center for Applied Math. My recent research focuses on automatic feature engineering and variable selection in the presence of heavy noise and multicolinearity.

Karan S.

I'm a second year Ph.D., advised by Prof. Elad Hazan. My research is focused on the design of interactive learning algorithms involving feedback-driven data collection. My recent work deals with complex, structured decision-making systems, involving partial feedback, ubiquitous in online advertising, clinical decision making. I graduated from the Indian Institute of Technology, Kanpur in 2015 with the distinction of being awarded the President's Gold Medal for the best academic performance. In 2014, as a research intern at Microsoft Research, Redmond, I worked on Programming-by-Natural-Language techniques to translate natural language prompts into structured queries over knowledge bases.

Mikhail K.

I am an MSE student in the Department of Computer Science interested in developing algorithms and models for computational problems. My research has focused on machine learning, natural language processing, mathematical optimization, scientific computing, and partial differential equations. I received an A.B. in Mathematics with Honors from Princeton University in 2016. My thesis was supervised by Professor Sanjeev Arora.

Nikunj S.

I am a first year Masters student in the Computer Science department. I am interested in Machine Learning, deep learning and NLP.

Oluwatosin A.

I am currently a First-year Master's CS student. My undergraduate degree was in Electrical Engineering (summa cum laude) at The George Washington University. So the world of CS (especially AI) is relatively new to me. I find it interesting to learn about topics in different subject areas, and I am hoping to learn with and contribute to the Princeton team with my skills and persistence.

Sanjeev Arora - Faculty advisor

Professor of Computer Science, Princeton University. Interests include Theory, Algorithms, Machine Learning and NLP.

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Applied Scientist, EU GTS RAS, GTS RAS
LU, Luxembourg
Have you ever wished to build high standard Operations Research and Machine Learning algorithms to optimize one of the most complex logistics network? Have you ever ordered a product on Amazon websites and wondered how it got delivered to you so fast, and what kinds of algorithms & processes are running behind the scenes to power the whole operation? If so, this role is for you. The team: Global transportation services, Research and applied science - Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, as surpassing their expectations is our passion. We improve customer experience through continuously optimizing the complex movements of goods from vendors to customers throughout Europe. - Global transportation analytical teams are transversal centers of expertise, composed of engineers, analysts, scientists, technical program managers and developers. We are focused on Amazon most complex problems, processes and decisions. We work with fulfillment centers, transportation, software developers, finance and retail teams across the world, to improve our logistic infrastructure and algorithms. - GTS RAS is one of those Global transportation scientific team. We are obsessed by delivering state of the art OR and ML tools to support the rethinking of our advanced end-to-end supply chain. Our overall mission is simple: we want to implement the best logistics network, so Amazon can be the place where our customers can be delivered the next-day. The role: Applied scientist, speed and long term network design The person in this role will have end-to-end ownership on augmenting RAS Operation Research and Machine Learning modeling tools. They will help understand where are the constraints in our transportation network, and how we can remove them to make faster deliveries at a lower cost. Concretely, you will be responsible for designing and implementing state-of-the-art algorithmic in transportation planning and network design, to expand the scope of our Operations Research and Machine Learning tools, to reflect the constantly evolving constraints in our network. You will enable the creation of a product that drives ever-greater automation, scalability and optimization of every aspect of transportation, planning the best network and modeling the constraints that prevent us from offering more speed to our customer, to maximize the utilization of the associated resources. The impact of your work will be in the Amazon EU global network. The product you will build will span across multiple organizations that play a role in Amazon’s operations and transportation and the shopping experience we deliver to customer. Those stakeholders include fulfilment operations and transportation teams; scientists and developers, and product managers. You will understand those teams constraints, to include them in your product; you will discuss with technical teams across the organization to understand the existing tools and assess the opportunity to integrate them in your product. You will also be challenged to think several steps ahead so that the solutions you are building today will scale well with future growth and objective (e.g.: sustainability). You will engage with fellow scientists across the globe, to discuss the solutions they have implemented and share your peculiar expertise with them. This is a critical role and will require an aptitude for independent initiative and the ability to drive innovation in transportation planning and network design. Successful candidates should be able to design and implement high quality algorithm solutions, using state-of-the art Operations Research and Machine Learning techniques. You will have the opportunity to thrive in a highly collaborative, creative, analytical, and fast-paced environment oriented around building the world’s most flexible and effective transportation planning and network design management technology. Key job responsibilities - Engage with stakeholders to understand what prevents them to build a better transportation network for Amazon - Review literature to identify similar problems, or new solving techniques - Build the mathematical model representing your problem - Implement light version of the model, to gather early feed-back from your stakeholders and fellow scientists - Implement the final product, leveraging the highest development standards - Share your work in internal and external conferences - Train on the newest techniques available in your field, to ensure the team stays at the highest bar About the team GTS Research and Applied Science is a team of 15 scientists and engineers whom mission is to build the best decision support tools for strategic decisions. We model and optimize Amazon end-to-end operations. The team is composed of enthusiastic members, that love to discuss any scientific problem, foster new ideas and think out of the box. We are eager to support each others and share our unique knowledge to our colleagues.
Applied Scientist, Prime Video Sports
IL, Haifa
Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are looking for an Applied Scientist to embark on our journey to build a Prime Video Sports tech team in Israel from ground up. Our team will focus on developing products to allow for personalizing the customers’ experience and providing them real-time insights and revolutionary experiences using Computer Vision (CV) and Machine Learning (ML). You will get a chance to work on greenfield, cutting-edge and large-scale engineering and science projects, and a rare opportunity to be one of the founders of the Israel Prime Video Sports tech team in Israel. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Computer Vision or Recommendation Systems to lead development of new algorithms and E2E solutions. You will be part of a team of applied scientists and software development engineers responsible for research, design, development and deployment of algorithms into production pipelines. As a technologist, you will also drive publications of original work in top-tier conferences in Computer Vision and Machine Learning. You will be expected to deal with ambiguity! We're looking for someone with outstanding analytical abilities and someone comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go. About the team In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.
Data Scientist, Workforce Solutions
US, WA, Seattle
The PeopleInsight (PI) org focuses on improving employee experience at Amazon, driving productivity and retention, and resulting in a motivated workforce of over 1.5 million associates and corporate employees. These are the questions we ask — Are we facilitating the right conversations to build an engaged workforce? What trends are we seeing in our employee data and what should managers do about it? How do we solve customer problems in the most efficient way possible? If these challenges sound interesting to you, you want to be a part of building ‘first of their kind’ products, and you are passionate about putting employee experience first, consider the PeopleInsight team. PI helps Amazon drive improvements in employee talent outcomes (e.g., job satisfaction and retention), and strive to be Earth’s Best Employer through scalable technology. PI is looking for a customer-obsessed Data Scientist for Employee Engagement Services, a suite of internal employee engagement and recognition products supporting Amazonians WW, with a strong track record of delivering results and proven research experience. This role will own and execute strategic cross-functional employee engagement experiments, analysis and research initiatives across Operations and Corporate audiences for high CSAT products. The Data Scientist must love extracting, cleaning and transforming high volume of data into actionable business information and be able to drive actionable insights. The data scientist will partner with Product, UX and Dev teams to own end-to-end business problems and metrics with a direct impact on employee experience. Success in this role will include influencing within your team and mentoring peers. The problems you will consider will be difficult to solve and often require a range of data science methodologies combined with subject matter expertise. You will need to be capable of gathering and using complex data set across domains. You will deliver artifacts on medium size projects, define the methodology, and own the analysis. Your findings will affect important business decisions. Solut Key job responsibilities • Implement statistical methods to solve specific business problems utilizing code (Python, R, Scala, etc.). • Development of user classification models and other predictive models to enable a personalized experience for a user. • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. • Collaborate with product management, software developers, data engineering, and business leaders to define product requirements, provide analytical support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models. • Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance. • Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations. • Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology About the team The PeopleInsight team is a collaborative group of Business Intelligence Engineers, Data Scientists, Data Engineers, Research Scientists, Product Managers, Software Development Engineers, Designers and Researchers that studies a workforce numbering in the hundreds of thousands. Our work is dedicated to empowering leaders and enabling action through data and science to improve the workplace experience of associates and ensure Amazon is Earth's Best Employer.
Applied Scientist - Computer Vision, Amazon Robotics
US, WA, Seattle
Do you want to create the greatest-possible worldwide impact in Robotics? Amazon has the world's most exciting treasure trove of robotics challenges. At Amazon Robotics we build high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. Amazon Robotics invents and scales AI systems for robotics in fulfillment. Our mission is to enable robots to interact safely, efficiently, and fluently high density real-world fulfillment centers. Our AI solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself. We hire and develop collaborative subject matter experts in AI with a focus on computer vision, deep learning, semi-supervised and unsupervised learning. We target high-impact algorithmic unlocks in areas such as scene and activity understanding, large scale generative models, closed-loop control, robotic grasping and manipulation—all of which have high-value impact for our current and future fulfillment networks. We are seeking a hands-on, seasoned Applied Scientists who will be deep in code and algorithms; who are technically strong in building scalable vision systems across item understanding, pose estimation, class imbalanced classifiers, identification and segmentation. As a Applied Scientist, you will contribute to the research and development of advanced robotic systems; your work along with other top-notch scientists and engineers will deliver the world's most scalable and robust robotic systems. You will drive ideas to products using paradigms such as deep learning, semi supervised learning and active learning. As a Applied Scientist, you will also help lead and mentor our team of applied scientists and engineers. You will take on challenging customer problems, distill customer requirements, and then deliver solutions that either leverage existing academic and industrial 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 implementation while you lead. A successful candidate has excellent technical depth, scientific vision, project management skills, great communication skills, and a drive to achieve results in a collaborative team environment. You should enjoy the process of solving real-world 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 AI and robotics to significantly impact the lives of millions of consumers. Key job responsibilities Architect, design, and implement Machine Learning models for vision systems on robotic platforms Optimize, deploy, and support at scale ML models on the edge. Influence the team's strategy and contribute to long-term vision and roadmap. Work with stakeholders across , science, and operations teams to iterate on design and implementation. Maintain high standards by participating in reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement. Prototype and test concepts or features, both through simulation and emulators and with live robotic equipment Work directly with customers and partners to test prototypes and incorporate feedback Mentor other engineer team members. A day in the life Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Sr. Research Scientist, Prime Air Navigation
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We are seeking a highly skilled Navigation Scientist to help develop advanced algorithms and software for our Prime Air delivery drone program. In this role, you will conduct comprehensive navigation analysis to support cross-functional decision-making, define system architecture and requirements, contribute to the development of flight algorithms, and actively identify innovative technological opportunities that will drive significant enhancements to meet our customers' evolving demands. Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.
Data Scientist , ADSP: Campaign & Creative
GB, London
How can Amazon improve the advertising experience for customers around the world? How can we help advertisers and customers find each other in a meaningful way? Amazon Advertising creates and transforms the connection between retailers/service providers and customers. Our teams strive to reinvent the way advertisers and agencies build brands and drive performance in their advertising. By using Amazon's foundation in e-commerce, we help brands connect with the right customers through creative solutions and formats across screens and devices, and in the physical world. Amazon Advertising seeks a Data Scientist with strong Data Analysis skills to join the ADSP engineering team split across Edinburgh and London. We make Guidance products that help optimise our customer's advertising campaign workflows and performance. As a scientist on the team, you will be involved in many aspects of the process - from idea generation, business analysis and scientific research, through to development - giving you a real sense of ownership. The systems that you help to build will operate at massive scale to advertising customers around the world. Our ideal candidate is an experienced Data scientist who has a track-record of performing analysis, applying statistical techniques and building basic ML models to solve real business problems, who has great leadership and communication skills, and who is motivated to achieve results in a fast-paced environment. Key job responsibilities Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment. Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. Promote the culture of experimentation at Amazon.
Applied Scientist
US, NY, New York
Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! 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.
Applied Scientist AGI AfroTech, Artificial General Intelligence
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team
Data Scientist, Consumables (消費財事業部)
JP, 13, Tokyo
Amazon Japan is seeking an experienced Sr. Data Scientist to join our growing team. In this critical role, you will leverage your strong quantitative and analytical skills to drive data-driven insights that shape our FMCG (fast-moving consumer goods) business and other key strategic initiatives. Your responsibilities will include: - Solving complex, ambiguous business problems using appropriate statistical methodologies, modeling techniques, and data science best practices to lead business insights for FMCG business growth. You will work closely with cross-functional partners to translate business requirements into actionable data science solutions. - Designing and implementing scalable, reliable, and efficient data pipelines to extract valuable insights from diverse data sources. This includes making appropriate trade-offs between short-term and long-term needs. - Communicating your findings and recommendations clearly and persuasively to technical and non-technical stakeholders. You will document your work to the highest standards and ensure your solutions have a measurable impact on the business. - Mentoring and developing more junior data scientists on your team. You will actively participate in the hiring process and contribute to the growth of Amazon's data science community. - Staying abreast of the latest advancements in data science and applying innovative techniques where appropriate to tackle challenging business problems.
Applied Scientist, Amazon
US, WA, Seattle
We are seeking a talented applied researcher to join the Whole Page Planning and Optimization (WPPO) Science team in Search. The latest data from Business Insider shows that almost 50% of online shoppers visit Amazon first. The Search WPPO Science team is responsible for developing reinforcement learning systems for the next generation Amazon shopping experience and delivering it to millions of customers. We believe that shopping on Amazon should be simple, delightful, and full of WOW moments for EVERYONE, whether you are technically savvy or new to online shopping. As an Applied Scientist, you will be working closely with a team of applied scientists and engineers to build systems that shape the future of Amazon's shopping experience by automatically generating relevant content and building a whole page experience that is coherent, dynamic, and interesting. You will improve ranking and optimization in our algorithm. You will participate in driving features from idea to deployment, and your work will directly impact millions of customers. You are going to love this job because you will: * Apply state-of-the-art Machine Learning (ML) algorithms, including Deep Learning and Reinforcement Learning, to improve hundreds of millions of customers’ shopping experience. * Have measurable business impact using A/B testing. * Work in a dynamic team that provides continuous opportunities for learning and growth. * Work with leaders in the field of machine learning.
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