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Senior Applied Scientist

Job ID: 1747311 | Services LLC


The GSF (Global Specialty Fulfillment) organization leads the innovation of Amazon’s ultra-fast fulfillment initiatives. We are an Operations org that hires and manages associates for ultra-fast businesses such as online grocery delivery, sub-same day delivery etc. GSFTech sits within GSF with the mission to build world-class automated Science-Tech products that enable ultra-fast delivery speeds for Amazon customers and job market opportunities for Amazon associates. Our key vision is to transform the online experience. We’re growing in scale and volume, by orders of magnitude. We are a team of passionate tech builders who work endlessly to make life better for our associates through amazing, thoughtful, and creative new scheduling experiences. To succeed, we need senior technical leaders to forge a path into the future by building innovative, maintainable, and scalable systems.

At Amazon, we are constantly inventing and re-inventing to be the most associate-centric company in the world. To get there, we need exceptionally talented, bright, and driven people. Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers.

We are looking for a Senior Applied Scientist who will be the science lead for all key ML and forecasting initiatives, responsible for building models and prototypes for labor planning systems, and will require close collaboration with other scientists on the team that are developing state-of-the-art optimization algorithms to scale. This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping/simulation, to implementation by working closely with colleagues in engineering, product management, operations, retail and finance.

As a Senior member of the scientist team, you will play an integral part on our Operations org with the following technical and leadership responsibilities:
· Help the team define the forward looking Science roadmap and vision by helping to identify, disambiguate and seek out new opportunities
· Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements
· Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization
· Develop scalable models to derive optimal or near-optimal solutions to existing and new scheduling challenges
· Create prototypes and simulations to test devised solutions
· Advocate technical solutions to business stakeholders, engineering teams, as well as executive-level decision makers
· Work closely with engineers to integrate prototypes into production system
· Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features
· Mentor and supervise the work of junior scientists on the team for technical development and their career development and growth
· Present business cases and document models, analyses, and their results in order to influence important decisions


· Ph.D. degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
· 3+ years of experience in building machine learning models for business application
· Experience programming in Java, C++, Python or related language
MS or PhD in Artificial Intelligence, Computer Science, Physics, Statistics, Applied Math, or Operations Research


· 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