Machine learning scientist, amazon

Machine learning scientist, amazon DEFAULT

Machine learning

Applied Scientist I, Consumer Payments

Job summaryAre you excited about influencing the payment experience of millions of customers worldwide ? The moment a customer makes a payment on Amazon is when trust is established – trust that the item is delivered on time, a refund is provided quickly if needed, a digital movie purchased will play immediately, a seller receives their disbursement, and hundreds of other experiences across Amazon when a customer completes a payment. The Payment Acceptance & Experience (PAE) team, within the Consumer Payments organization, has the mission to build the most trusted, intuitive, and accessible payment experience on Earth. Applied Science & Machine Learning Engineering (PAE ASMLE) is the core machine learning team within PAE. The team has a mission to enhance customer payments experience that requires advancing the state of the art in machine learning. We work backwards from the customer to create value for them by leveraging an underlying applied science methodology. We deploy our solutions through Native AWS services that operate at Amazon scale. We strive to publish our solutions and share our findings so that the broader Amazon scientific community can benefit.As an applied scientist on our team, your role is to leverage your strong background in Computer Science and Machine Learning to help build the next generation of our model development and assessment pipeline, harness and explain rich data at Amazon scale, and provide automated insights to improve machine learned solution that impacts Payments experience of millions of customers every day. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and applying science to various business contexts. We are particularly interested in experience applying predictive modeling, natural language processing, deep learning, and reinforcement learning at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.Your responsibilities include:. Analyze the data and metrics resulting from traffic into Amazon Consumer Payments experiences.. Design, build, and deploy effective and innovative ML solutions to improve various components of the Consumer Payments experience, using predictive modeling, recommendations, anomaly detection, ranking, and forecasting.. Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.. Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR/Forecasting.Your benefits include:. Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers.. The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems.. Excellent opportunities, and ample support, for career growth, development, and mentorship.. Competitive compensation, including relocation support.The PAE ML team operates primarily out of Amazon's Seattle office. We are a new and expanding team where you will have an opportunity to influence our goals and mission. We collaborate with Software Engineering, Data Engineering, Product Management and Marketing teams within Amazon Consumer Payments to solve and deploy machine learning solutions at scale.Please visit https://www.amazon.science for more information

Sours: https://www.amazon.science/research-areas/machine-learning

DESCRIPTION

Are you interested to disrupt and redefine the way customers buy Beauty products online? Are you interested in using the latest advances in machine learning, computer vision, and augmented reality to build online customer experiences for Beauty products that can equal or even surpass an in-store experience?

We are looking for talented and innovation-driven scientists who are passionate about building improved customer experiences by leveraging data-science and machine-learning technologies. You will have an opportunity to revolutionize the customer shopping experience across the world's most extensive catalog of beauty products. You will be directly responsible for leveraging machine-learning/computer-vision algorithms and data-science techniques to drive innovation. You will collaborate with product managers, software engineers, UX designers, scientists, and the broader Amazon tech community to build solutions that enhance the beauty shopping experience across all surfaces, including desktop, mobile devices, and other Amazon devices.


About the team

The Amazon Beauty Tech is a brand-new team that is rapidly expanding. We are a small group of engineers, scientists, product managers, and designers who drive technological innovation to improve customer experience. We have a startup-like work culture where innovation is encouraged; we are never afraid to propose grand ideas for fear of failing!

We build:
· Computer vision and augmented reality (AR) experiences: We bring exciting experiences directly to the customer's mobile phone using their cameras and combinations of facial recognition and AR.
· Personalization using machine learning: We will be working with machine learning (ML) technologies such as data classification and reinforced learning models to provide better-personalized shopping experiences.
· Elevated customer experiences: We will create beautiful and dynamic customer experiences that require deep knowledge of relevant UI technologies and user-centric design patterns.
· Amazon scale systems: All our technology needs to work at Amazon scale, serving millions of customers with millisecond-level latency.
· Data pipeline and analytics tools: Amazon is data-driven, and a robust data backbone is necessary for our systems. We build on robust and scalable data pipelines and tools using core AWS services.

BASIC QUALIFICATIONS

· Bachelor’s degree in Computer Science, Statistics, Data Science, or any other quantitative field.
· 2+ years of non-internship professional experience with machine learning, statistical modeling, data mining, and/or analytics techniques.
· 2+ years of experience with Python, R, or other scripting languages.
· Advanced ability to draw insights from data and clearly communicate them (verbal/written) to the stakeholders and senior management.

PREFERRED QUALIFICATIONS

· Master’s degree or PhD in a highly quantitative field (Machine Learning, Statistics, Data Science, Math, etc.).
· Experience applying various machine learning techniques, and understanding the key parameters that affect their performance.
· Familiarity with deep learning algorithms and/or computer vision.
· Familiarity with at least 1-2 popular AI/ML frameworks and tools - TensorFlow, PyTorch, MXNet, scikit-learn, OpenCV, ARCore, and ARKit.
· Expertise in estimation, experimental design, hypothesis, and A/B testing.
· Experience partnering with engineering teams to build and test production systems.
· Familiarity with AWS services such as EC2, DynamoDB, RDS, AWS Lambda, and Amazon SageMaker.
· Ability to achieve stretch goals in a highly innovative and startup-like environment.

Sours: https://www.amazon.jobs/en/jobs/1508287/machine-learning-scientist
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DESCRIPTION


Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by automatically mitigating risk and providing support solutions?


Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? A

re you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-art algorithms to solve real world problems?


Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify tasks and processes?


If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Customer Trust and Partner Support group.

Major responsibilities
· Use statistical and machine learning techniques to create the next generation of scalable risk management and support systems.
· Analyze and understand large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends.
· Design, development and evaluation of highly innovative models for risk management.
· Work closely with teams of scientists and software engineers to drive real-time model implementations and new feature creations.
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
· Research and implement novel machine learning and statistical approaches.

Please visit https://www.amazon.science for more information

BASIC QUALIFICATIONS

· A MS in CS, Machine Learning, Statistics, Operations Research or in a highly quantitative field
· 4+ years of hands-on experience in predictive modeling and large data analysis
· Strong ML breadth and depth
· Strong skills with SQL
· Strong skills with Python/Spark/Perl (or similar)
· Communication and data presentation skills
· Strong problem solving ability

PREFERRED QUALIFICATIONS

· A PhD in CS, Machine Learning, Statistics, Operations Research
· 6+ years of industry experience in predictive modeling and analysis
· Superior ML breadth and depth
· Expert skills with SQL
· Expert skills with Spark/Python/Perl (or similar)
· Superior problem solving ability
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us

Sours: https://jobs-us-west.amazon.com/en/jobs/1399181/sr-machine-learning-scientist
Introduction to Amazon SageMaker

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Amazon machine learning scientist

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How to Prepare for your Applied Scientist Interview at Amazon

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