Data Scientist
Cognomotiv
(US-only candidates)
From entertainment to autonomous driving, the complexity of modern vehicles is increasing at a breathtaking rate, with the growing role of software as more and more functionality is shifted from electronics and mechanical systems to software-controlled systems. These advancements and increased complexity bring new vulnerabilities, such as cyberattacks or mechanical/software failures. At Cognomotiv, we develop state-of-the-art algorithms and model the systems using a hybrid of edge and cloud computing, in order to guarantee the safety and reliability of any vehicle you step into.
CHAI (Cognomotiv Hybrid AI) is a highly optimized blend of edge and cloud AI that effectively performs non-intrusive system diagnosis, prognosis, and makes recommendations with powerful and efficient native models. CHAI models are unique in their ability to perform and report sophisticated fault and failure detection and prediction in a resource-constrained environment. Additionally, these models are seamlessly coupled and continuously improved with our powerful composite and distributed learning infrastructure.
Description
We are seeking an ambitious, self-reliant data scientist to:
• Optimize and test ML and statistical models to report and predict vehicle health in a variety of subsystems, including mechanical, sensor, and onboard computers.
• Research and develop methods for anomaly detection, diagnosis, and ultimately root cause analysis using vehicle data streams.
• Design and/or implement models to detect breaches in-vehicle 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.
Ideal candidates 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 to millions.
Required Education & Skills:
• Degree (advanced preferred) in a quantitative field such as statistics or physics
• Proficiency in large-scale data interaction -- SQL, Hadoop, etc.
• Expert knowledge of one or more scripting languages (e.g. Python)
• 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
Ideal candidates independently recognize needs/possibilities and provide creative and practical solutions.
Cognomotiv
(US-only candidates)
From entertainment to autonomous driving, the complexity of modern vehicles is increasing at a breathtaking rate, with the growing role of software as more and more functionality is shifted from electronics and mechanical systems to software-controlled systems. These advancements and increased complexity bring new vulnerabilities, such as cyberattacks or mechanical/software failures. At Cognomotiv, we develop state-of-the-art algorithms and model the systems using a hybrid of edge and cloud computing, in order to guarantee the safety and reliability of any vehicle you step into.
CHAI (Cognomotiv Hybrid AI) is a highly optimized blend of edge and cloud AI that effectively performs non-intrusive system diagnosis, prognosis, and makes recommendations with powerful and efficient native models. CHAI models are unique in their ability to perform and report sophisticated fault and failure detection and prediction in a resource-constrained environment. Additionally, these models are seamlessly coupled and continuously improved with our powerful composite and distributed learning infrastructure.
Description
We are seeking an ambitious, self-reliant data scientist to:
• Optimize and test ML and statistical models to report and predict vehicle health in a variety of subsystems, including mechanical, sensor, and onboard computers.
• Research and develop methods for anomaly detection, diagnosis, and ultimately root cause analysis using vehicle data streams.
• Design and/or implement models to detect breaches in-vehicle 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.
Ideal candidates 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 to millions.
Required Education & Skills:
• Degree (advanced preferred) in a quantitative field such as statistics or physics
• Proficiency in large-scale data interaction -- SQL, Hadoop, etc.
• Expert knowledge of one or more scripting languages (e.g. Python)
• 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
Ideal candidates independently recognize needs/possibilities and provide creative and practical solutions.