Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
  • This site is mobile friendly. You do not need a log-in or password to access information.
  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
  • The site is refreshed daily to remove out-of-date content.
  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.

Job Information

Amazon Sr. Applied Scientist, Amazon Japan Store Tech in 31, China

Description

Amazon Japan Store Tech (JST) Science team serves as the core science division of JP Store Tech, with the vision to enable and accelerate the best-in-class CX through state-of-the-art machine learning technologies. This team owns the science vision definition, science roadmap planning, and science solution delivery in key business areas in Japan including Search, Customer Growth and Engagement, Personalization and Delivery.

As a Senior Applied Scientist, you will lead the team to create the science long-term vision and roadmap across multiple business domains. You will lead the design, implement and deliver models on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.

Key job responsibilities

  • Initiate and drive the design and delivery of science solutions or systems that address significantly large or endemic customer and business problems, and directly impact the goals of your entire organization, and possibly others.

  • Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve business problems.

  • Analyzing data and metrics identify new science opportunities.

  • Working with teams worldwide on global projects.

  • Recognized by internal and external peers as a thought leader in your area(s) of scientific expertise. You publish your results at top academic conferences and engage with the academic community.

A day in the life

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 with tangible customer impact

  • Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

We are open to hiring candidates to work out of one of the following locations:

Beijing, 11, CHN | Shanghai, 31, CHN

Basic Qualifications

  • 3+ years of building machine learning models for business application experience

  • PhD, or Master's degree and 6+ years of applied research experience

  • Experience programming in Java, C++, Python or related language

  • Experience with neural deep learning methods and machine learning

Preferred Qualifications

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

  • Experience with large scale distributed systems such as Hadoop, Spark etc.

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