Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon's Retail business? This job for you! The Customer Behavior Analytics (CBA) team, in partnership with the F3(Fresh/Food/Fast) team, is looking for motivated individuals with strong analytical skills to help drive the expansion of F3 business globally. The CBA team is responsible for the architecture, design, implementation of tools used to understand customer behavior and value generation for F3 investments. Come and join us!
Amazon’s CBA team is looking for Applied Scientists, who can work at the intersection of machine learning, statistics and economics; and leverage the power of big data to solve complex problems like long-term causal effect estimation.
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.
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.
- Excellent opportunities, and ample support, for career growth, development, and mentorship.
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.
- Collaborate with product managers and engineering teams to design and implement solutions for Amazon problems
- 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.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
Basic Qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred Qualifications
- Experience using Unix/Linux
- Experience in professional software development
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.