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Applied Scientist en Barcelona

... Do you enjoy solving deep technical problems and building innovative solutions? Do you thrive working in a fast paced environment? And, do you like working with smart, passionate colleagues? If your answers were yes,...

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DESCRIPTION

Do you enjoy solving deep technical problems and building innovative solutions? Do you thrive working in a fast paced environment? And, do you like working with smart, passionate colleagues? If your answers were yes, this can be the role for you.

Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience – from checkout on the website, to shipment planning, fulfillment, and delivery. Our software systems include services that use thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over 100 million online shoppers. With rapid expansion into new geographies, innovations in supply chain and delivery models, with an increasingly complex transportation network, an ever expanding selection of products, and a growing number of shipments worldwide; we have an opportunity to build software that scales the business, leads the industry through innovation, and delights millions of customers worldwide. We leverage cutting edge technologies in big data, machine learning, real time analytics, and high volume, low latency, high availability services.

Amazon Transportation Services (ATS) is looking for an Applied Scientist to work on machine learning models that will directly impact how our services prevent, detect, and solve real-time problems; and, how our transportation planning models function worldwide. The main focus of ATS is to account for all network constraints, while maximizing the number of shipments shipped, minimizing cost, providing a variety of delivery options, and maximizing delivery performance. You will help build new services and redefine the way whole operational units work, while using new technologies that improve usability and increase performance and scalability. You will have an opportunity to work with a wide range of teams and services across Amazon, and work alongside a core team of applied/data scientists, and software developers, working on optimization and machine learning models and applications.

If you are an experienced Applied Scientist who has a strong academic background, who has a knack for understanding and solving real-world problems, who enjoys developing and deploying ML/DL models into production, who loves to innovate and deliver results, and who is interested in re-engineering and delivering new services to help fuel the explosive growth of ATS, then we want you to be on our team.

BASIC QUALIFICATIONS

· PhD in Computer Sciences, Mathematics, or Statistics with specialization in machine learning (alternatively, MSc. and 3+ years in scientist role).
· Broad knowledge of fundamentals and the state-of-the art in relevant areas of Machine Learning/Artificial Intelligence/Data Science
· 2+ years of hands-on experience in predictive modeling and analysis, and in deploying machine learning models in production.
· Knowledge of Software Development (data structures, algorithms, etc.).
· Strong coding skills in Python.
· Strong problem solving skills.

PREFERRED QUALIFICATIONS

· Explicit (industry or academic) experience with NLP.
· Experience with Cloud Computing and Services such as AWS.
· Experience with programming languages such as Java, Scala, and/or others.
· Experience working effectively with science, data processing, and software engineering teams.
· Proven track record of innovation in creating novel algorithms and applying the state-of the-art.
· Experience with methods in the Reinforcement Learning domain.
· Strong verbal and written communication skills.
· Strong publication record.

Información extra

Status
Inactiva
Localización
Barcelona
Tipo de contrato
Tiempo completo
Carnet de conducir
No
Vehículo
No
Carta de motivación
No

Barcelona | Tiempo completo