Applied Scientist II, Customer Behavior Analytics

Are you seeking a setting where you can spearhead innovation? Do you wish to employ learning techniques and complex mathematical modeling to tackle real-world challenges? Interested in playing a crucial part in the future of Amazon's Retail business? This opportunity is for you! The Customer Behavior Analytics (CBA) group, in conjunction with the F3 (Fresh/Food/Fast) team, is on the lookout for driven individuals with excellent analytical abilities to fuel the global expansion of F3 business. The CBA team oversees the architecture, design, and implementation of tools for understanding customer behavior and generating value for F3 investments. Come and join us! Amazon's CBA team is seeking Applied Scientists capable of working at the crossroads of machine learning, statistics, and economics to harness the strength of big data in solving complicated problems such as long-term causal effect estimation. As an applied scientist, you will bring machine-learning advancements and statistical modeling to analyze data and devise customer-focused solutions in complex industrial environments. You'll be part of a fast-paced, cross-disciplinary team of researchers who are field leaders. You will be challenged with hard problems, decipher actual requirements, and create solutions that either leverage pre-existing academic and industrial research or employ your unique pragmatic thinking. This position calls for a practical technical leader comfortable with uncertainty, capable of simplifying complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and causal inference. We’re also looking for candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and excellent judgment. Your benefits include: - Working on a high-impact, high-visibility product, making the experience for millions of customers better. - The chance to use (and innovate) cutting-edge ML methods to solve real-world problems. - Outstanding opportunities and comprehensive support for career growth, development, and mentorship. Key job responsibilities - Understand and mine a vast amount of data, design and implement new learning algorithms and prediction techniques to improve the long-term causal estimation approach. - Collaborate with product managers and engineering teams to design and implement solutions for Amazon's problems. - Design, build, and launch effective and innovative ML solutions to enhance 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 the following locations: Seattle, WA, USA Basic Qualifications - 3+ years of experience in creating models for business application - PhD, or Master's degree and 4+ years of experience in CS, CE, ML or related field - Experience with patents or publications at top-tier peer-reviewed conferences or journals - Programming experience in Java, C++, Python or related language - Experience in any of these areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications - Experience using Unix/Linux - Professional software development experience 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 labor costs across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market to $222,200/year in our highest geographic market. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending 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.