Senior Applied Scientist, Aws Automated Reasoning

Amazon Amazon · Big Tech · London, United Kingdom · Applied Science

Senior Applied Scientist role at AWS focused on automated reasoning, privacy, and sovereignty solutions. The role involves solving complex problems, designing and implementing solutions with long-term impact, providing technical influence, developing strategic plans for new solutions, and mentoring others. Requires a Master's degree, programming experience, and experience with neural deep learning, machine learning, building ML models for business applications, and applied research.

What you'd actually do

  1. Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation.
  2. Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact.
  3. Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience.
  4. Develop strategic plans to identify fundamentally new solutions for business problems.
  5. Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues.

Skills

Required

  • Master's degree
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning
  • Experience in building machine learning models for business application
  • Experience in applied research

Nice to have

  • 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.

What the JD emphasized

  • deep knowledge and understanding of your domain
  • scientific innovation
  • long-term quantifiable impact
  • cross-organizational technical influence
  • fundamentally new solutions
  • mentoring

Other signals

  • automated reasoning
  • privacy
  • sovereignty
  • deep knowledge and understanding of your domain
  • scientific innovation
  • long-term quantifiable impact
  • cross-organizational technical influence
  • develop strategic plans
  • fundamentally new solutions
  • career development of others
  • mentoring
  • neural deep learning methods
  • machine learning
  • building machine learning models for business application
  • applied research