Amazon Applied Scientist CBA 

United States, Washington, Seattle 

995315763

As an applied scientist, you will bring statistical modeling and machine learning advancements to analyze data and develop customer-facing solutions in complex industrial settings. You will be working in a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and causal inference. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.Key job responsibilities
- Understand and mine the large amount of data, prototype and implement new learning algorithms and prediction techniques to improve long-term causal estimation approaches.- Design, build, and deploy effective and innovative ML solutions to improve various components of our ML and causal inference pipelines
- Publish and present your work at internal and external scientific venues in the fields of ML and causal inference.

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience building machine learning models or developing algorithms for business application
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in professional software development