Lead Data Scientist - RappiPay

[CL] Santiago de Chile

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Posted 4 weeks ago

The Team 
Our expectations are pretty high for data scientist positions. The Data Science team plays a leading role in solving our most challenging problems and guiding the decisions that we take around product, growth and operations. Information is only valuable when transformed into actionable insights, and it is through experimentation, high-tempo testing, rigorous measurement, and correct communication, that our teams achieve our audacious goal to establish Rappi as the super-app in LatAm.Your Impact, You will
Build, implement, and maintain machine learning systems in technology products. Lead engineering best practices for scaling ML and designing/building software that is reliable, scalable, and secureBe responsible for the implementation, testing, and release of a range of models, both for existing and “to-be-invented” use casesWork closely with Machine Learning scientists to design, code, train, test, deploy, iterate and own state-of-the-art systems for executing ML modelsBuilding end-to-end data pipelines to train, maintain, and track performance of our Machine Learning and Operations Research products
Talents You Bring To The Team
Deep knowledge of machine learning algorithms and understanding of feedback loopsYou are *highly proficient* in SQL and NoSQL query languagesAdvanced computer literacy and software engineer skills. Hands-on experience in  Python, JavaScript, Java & API integration, Scala and Apache SparkTrack record of developing web services or other large-scale distributed systemsYou embody our core values, ambition for a greater good, beauty in everything we do, fast execution and prioritization, and are eager to take risks and deliver magicProficiency training large scale models in at least one modern deep learning engine such as MXNet, Tensorflow, Caffe/Caffe2, Keras, PyTorch/Torch, and Theano is a plus
Job tags: Deep Learning Engineering Java JavaScript Keras Machine Learning ML MXNet NoSQL Python PyTorch Research Scala SQL TensorFlow Theano