Job Information
Amazon Senior Applied Scientist, Amazon Connect in New York, New York
Description
As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.
Interested in Machine Learning (ML) and Artificial Intelligence (AI)? Do you want to join the team that is building AI/ML features that will disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment?
Our team is leading the AI features of Amazon Connect. We are a team of scientists and AI/ML engineers working on multiple AI/ML projects, using state-of-the-art science and engineering practices to solve hard problems for our customers in the space of contact center operations, management and optimization.
Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is a publicly available service based on ten years of development building the tools Amazon itself uses to provide its award-winning customer service. With Amazon Connect, businesses can create their own cloud-based contact centers and begin taking calls in minutes. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.
We are looking for a Senior Applied Scientist (Machine Learning) with a strong academic background and industry experience in the areas of stochastic modeling, queueing theory, anomaly detection and optimization.
About the team
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.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred 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.
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.
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 and 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.
Basic Qualifications
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
4+ years of building machine learning models or developing algorithms for business application experience
Knowledge of programming languages such as C/C++, Python, Java or Perl
Deep knowledge stochastic analysis, queueing theory and optimization.
Preferred Qualifications
Experience with neural deep learning methods and machine learning
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Strong publication/scientific track record.
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.