Sr. Applied Scientist

Job ID: 1553820 | Services LLC


Interested in leading a new team involving data sciences, algorithm development (machine learning, natural language processing) and an opportunity to impact every Amazon customer?

The newly formed Reconciliation team is responsible for the critical services that assemble the product detail pages on the Amazon website by combining data from sellers, vendors or internal systems, in real-time, and millions of times a day. These services, which are a core part of the Amazon's catalog, are being re-built from scratch. The team offers a unique blend of hard machine learning and computer science problems (scalable distributed ML systems and high-performance natural language algorithms ) and an opportunity to help the businesses model their vision on the platform.

The Recon team is looking for an innovative and customer-focused applied scientist to help us make the world’s best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to pick best product facts that matter to our customers. You will work in a collaborative environment where you can experiment with massive data from the world’s largest product catalog, work on challenging problems, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers.

Successful candidates are passionate about translating high-level, ambiguous business goals to science problems that enable multiple businesses. You are comfortable taking initiative and working alongside and top-notch scientists.

Item Master is modernizing the Reconciliation algorithm and related services that determine what product details shows on every detail page. We're looking to build out a new team to solve some very hard engineering problems that include incorporating ML algorithms. This is an opportunity to have to huge impact as this platform is used by 3p sellers, Digital, Amazon Retail and is core to Amazon’s e-commerce business. If you enjoy working with really smart scientists, SDEs and Principals and on a team with low operations, let's talk soon!

Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

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· PhD degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
· 3+ years of experience in building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· MS in Computer Science or similar field and strong knowledge of machine learning.
· 5+ years of relevant experience in industry and/or academia OR PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
· 3+ years of experience programming with an object-oriented language (Python, C++, Java.
· Familiarity with a broad set of supervised and unsupervised ML approaches and techniques ranging from Regression to Deep Neural Networks.
· Proven track record of successfully applying ML-based solutions to complex problems in business, science, or engineering.


· PhD in Computer Science, strong knowledge of machine learning, and
· 5+ years of relevant experience in industry and/or academia OR PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
· Experience with fast prototyping.
· Experience working effectively with software engineering teams.
· Publications at top-tier peer-reviewed conferences or journals.
· Depth and breadth in state-of-the-art NLP, Text based Deep learning technologies.
· Good written and spoken communication skills.
· Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Spark, Hadoop, Map-Reduce).

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation