At BullGuard Israel, we make it simple to protect everything in your smart connected home. The Internet of Things (IoT) is expected to reach over 30 billion connected devices by 2020, of which over 43% will be used by consumers at home. We offer a custom-built solution to protect smart home WiFi network, giving our users the freedom to connect as many internet devices in their home without compromising on privacy and security.
We are proud to be featured in magazines and conferences around the world. Our multi-award winning product Dojo was awarded “Best Connected Consumer Device” at Mobile World Congress and also ranked by Forbes as one of the Best CES Products that will be hot in 2018.
Things are getting exciting at BullGuard, as we are growing at a rapid pace, and we’re just getting started! If you are motivated, intelligent, creative, and seek to work in a fast paced environment, this opportunity is for you!
As a Data Scientist at BullGuard Israel specializing in IoT BigData security, you will design, build and deploy big data driven solutions based on state of the art machine learning and AI algorithms. You will create and maintain an optimal and scaleble data pipelines architecture in real time environments.
·We are looking for a candidate with 3+ years of experience in a Data Science role
·B.Sc./M.Sc. in computer Science, computer engineering or related field
·Experience with stream-processing systems: Storm, Spark-Streaming, etc
·Highly experienced in Big Data platforms and solutions (EMR, Hive, etc)
·Knowledge & experience in Machine Learning Algorithms
·Experienced with data driven/oriented scaleble solutions using cloud services (preferably AWS)
·Experience in deployment and automation of Machine learning models in real time environments
·You have at least 2 years of experience with Scala and at least 1 year of experience in Python
·Deep knowledge & experience with Apache Spark (SQL, Streaming, ML)
·Deep knowledge & experience with Apache Kafka
·Statistical scripting Code – R
·Familiarity with JVM applications
·Hand on experience in design and deployment of anomaly detection algorithms
·Experience in Deep learning using Tensorflow