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Senior data science engineer


This is a Full-time position in Edison, NJ posted November 29, 2019.

Cognomotiv’s MarketThe complexity of modern automobiles is increasing at breakneck speed.

The introduction of an array of brand-new features, along with refinements on old capabilities, has wildly expanded the role of software in today’s vehicles.

More and more functionality is shifting from electronic and mechanical systems to onboard computers controlled by software.

This trend is only accelerating: myriad new services rely heavily on vehicles being constantly online, and autonomy is becoming increasingly real.Software offers amazing new opportunity to the automotive world, but with it comes complexity that creates security vulnerabilities and operational failures due to underlying hardware or the software that controls it.Who We AreAt Cognomotiv, we help vehicle manufacturers and suppliers guarantee the safety and reliability of every vehicle on the road, thanks to state-of-the-art AI that leverages a hybrid of edge and backend computing to identify anomalous vehicle behavior in real time.Cognomotiv technology is a blend of edge and backend AI that performs non-intrusive system diagnosis and prognosis, and makes remediation recommendations with powerful and efficient native models.

Our AI is unique in its ability to perform fault and failure detection and prediction in a resource-constrained environment.DescriptionWe are seeking an ambitious, self-reliant data science engineer who operates with a sense of urgency and has the ability to thrive in a fast-paced environment.

You will design and build the robust, supportable, highly scalable AI foundation of Cognomotiv’s solution:
● Optimize and test ML and statistical models to report and predict systems’ health in a variety of subsystems, including mechanical, sensor, and onboard computer.
● Research and develop methods for anomaly detection, failure diagnosis, and ultimately root cause analysis using systems data streams.
● Design and/or implement models to detect breaches in system cybersecurity.
● Organize and manage fleet data flow, storage, and automated procedures.
● Use cloud resources to mine fleet databases for fault patterns and precursors.
● Design and execute in-house mechanical, sensor, and computer experiments.
● Organize and clearly present or publish findings.
● Assist in porting models to native language for edge computation and learning.You possess deep technical skills that will be used to drive insights into new products, working closely with both data scientists and engineers. You will have the opportunity to synthesize learning from edge-trained models, a paradigm the entire IoT is striving for. You will have access to a new and rich dataset, and use it to directly provide safety and reliability to all automated systems.Education & Experience Requirements:
● Degree (advanced preferred) in a quantitative field such as statistics or physics
● 3+ years of industry experience in a data science role
● Proficiency in large scale data interaction SQL, Hadoop, etc.
● Expert knowledge of one more more scripting languages (e.g.

● Basic proficiency in at least one object-oriented programming language (e.g.

C++, Java)
● Solid understanding and working knowledge of fundamental probability and statistics
● Strong communication skills
● The ideal candidate can independently recognize needs/possibilities and provide creative solutions.