Senior Applied Scientist, Special Projects
Seattle, Washington, USA
Amazon.com
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Job summary
We are a team of doers working passionately to apply cutting-edge advances in technology to solve real-world problems. As a Senior Applied Scientist at the intersection of machine learning and the life sciences, you will participate in developing exciting products for customers. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the cutting edge of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams.
Location is flexible within the US.
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust
Work/life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future
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.
We are a team of doers working passionately to apply cutting-edge advances in technology to solve real-world problems. As a Senior Applied Scientist at the intersection of machine learning and the life sciences, you will participate in developing exciting products for customers. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the cutting edge of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams.
Location is flexible within the US.
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust
Work/life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future
Basic Qualifications
- PhD with 4 years of applied research experience or Masters degree and 6+ years of applied research experience
- 3+ years of building Machine Learning models to solve problems in the life sciences or physical sciences
- 2+ years of experience in software development in languages such as Python, R, C++, or Scala
- 2+ years experience with topics in ML such as Causal Learning, Deep Learning, Natural Language Processing, Transfer Learning, Bayesian Optimization, or Generative models
Preferred Qualifications
- Ph.D. in Computer Science, Machine Learning, Statistics or a related quantitative field
- 5+ years of practical experience applying ML to solve complex problems in an applied environment
- Significant peer-reviewed scientific contributions in premier journals and conferences
- Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
- Experience with defining research and development practices in an applied environment
- Proven track record in technically leading and mentoring scientists
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
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.
Tags: Bayesian Computer Science Deep Learning Generative modeling Machine Learning ML models NLP PhD Python R Research Scala Statistics
Perks/benefits: Career development Conferences Flex hours Startup environment
Region:
North America
Country:
United States
Job stats:
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Category:
Data Science Jobs
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