Applied Scientist – Algorithms and ML

Job ID: 1516667 | Project Celeste

DESCRIPTION

We are a passionate team of doers that apply cutting-edge advances in technology to solve real-world problems and transform our customers’ experiences in ways we can’t even imagine yet. As an Applied Scientist, you will be working with a unique and gifted team developing exciting products for customers and collaborating with cross-functional teams.

Responsibilities
· Collaborate across functions to , develop and implement algorithms to solve high-impact problems
· Evaluate statistical modeling and Machine Learning approaches using historical data
· Define requirements and measurement criteria for scientific and machine learning models.
· Translate model prototypes into secure, stable, testable, and maintainable production services.
· Develop automated approaches towards monitoring model performance and evaluating impact.
· Encourage and support knowledge-sharing within team and external groups
· Responsible for influencing technical decisions in areas of /modelling that you identify as critical future offerings
· Deliver algorithm and ML projects from beginning to end, including understanding the customer needs, aggregating data, exploring data, building & validating predictive models, and deploying completed models.


Amazon is looking for an Applied Scientist to join an exciting new project team working to build a completely new, best in class . Our team is fast paced, highly collaborative and is organized like a startup.

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.

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 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.

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.

Our main office is Milpitas Ca but other US-based Amazon centers are ok.

BASIC QUALIFICATIONS

· Master's degree in Computer Science, Computer Engineering, in Statistics, mathematics, bioinformatics or equivalent experience.
· 3+ years of Experience with machine learning algorithms, probabilistic models, and general statistical modeling
· Experience programming in Java, C++, or related language

PREFERRED QUALIFICATIONS

· PhD degree in Statistics, Applied Math, Computer Science, Computer Engineering, bioinformatics or a related quantitative field with at least 4+ years of working experience as an Applied Scientist.
· Experience in biological sciences and bioinformatics analysis
· Background in predictive algorithms is a plus
· Expertise in communicating insights from complex data to both scientific peers and business leaders through technical writing and visualization.
· Ability to collaborate effectively in a fast moving environment with complex dependencies and requirements.
· Proficient in a statistical modeling framework like R, , Matlab, Scala, or .
· Experience with at least one of the modern distributed ML frameworks such as TensorFlow, PyTorch, MxNet
· Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
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, visit US Disability Accommodations.