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Data Scientists Analysts Sep 27, 2018
Dearborn, MI 48124  
Position Description:
• Participates in feasibility assessment of prioritized features in collaboration with cross-functional teams and develops feature recommendations for connected vehicle feature content along with identifying target vehicle program and region by considering technical risks and conducting cost/benefit analysis. • Develops/supports “feature roadmaps” closely working with feature engineering leads within CVP&P and with feature champions across various skill teams. • Asses data quality and create data transformations, collaborate to support data collection, integration, and retention requirements based on the collected input. • Work closely with business partners to identify and answer important business and product questions. Communicate insights to executive leadership. • Works with a team of architects and engineers to breakdown connected vehicle feature into manageable chunks of functional components and distribute them across Vehicle, Cloud and Mobile App sub-systems / components. • Collaborate with GDI&A and CVP&P feature teams to bring new connected vehicle concepts into production. • Works with cross functional groups to develop interoperability interfaces across sub systems and translate them into system level requirements for building connected vehicle systems and data architecture. • Collaborate with IT (business, solution and information) architecture counter parts to align business vision to the technical solutions for connected vehicle features. • Integrate with vehicle component engineering team to collaborate and develop connectivity platform approach through promoting reusable design solutions across several vehicle electronic components.
Skills Required:
• Strong analytical and problem solving skills with the ability to navigate through working teams across multiple departments. • Knowledge of core engineering fundamentals. General understanding of interoperability techniques and standards for enterprise information technology systems, mobile applications & in-vehicle embedded systems and ability to work through the constraints of various systems is required. • Experience identifying solutions that leverage existing systems and assets, with creative solution definition methodology and focus on end-to-end lifecycle of the product/feature. • Broad knowledge of Service Oriented Architecture and experience with Enterprise Application Integration patterns and understanding of embedded software design. • Experience with cloud based application integration, enterprise application integration and service oriented architecture concepts and micro services architecture principles. • Research, evaluate, implement, and present statistical and machine learning methods to provide actionable insights. • Research, design and implement data models and cutting edge algorithms to analyze diverse sources of data and demonstrated skills in manipulation and dealing with large structured and unstructured data sets. • Programming experience in one or more of the languages like Matlab, R, Python, C. • Experience with tools such as: SQL, Hadoop, Teradata, SAS, Excel, Access, etc. • Ability to work with large cross-functional teams under aggressive timelines and sporadic heavy workloads. • Ability to prioritize tasks on hand by evaluating long-term implications and develop product and platform roadmaps. • Ability to present technical artifacts at varying degrees of technical depth to a wide range of audience. • Ability to drive technology innovation through collaboration across advanced engineering and IT teams.
Skills Preferred:
• Knowledge and experience with vehicle architectures, CAN/Automotive Ethernet, diagnostics, embedded device messaging and interoperability of embedded components. • Knowledge of embedded system integration with head units, radios and vehicle HMI as well as understanding of customer experience with mobile devices. • Knowledge of embedded software architecture and design. • Broad understanding of enterprise IT systems and their interoperability mechanisms including vehicle to cloud connectivity, cloud computing, Internet of Things, API management, mobile app architecture, and multi-channel distributed system integration. • Understanding of embedded module architecture: Microcontrollers, Flash, RAM, device drivers… etc. • Understanding of Bluetooth stack, TCP/IP network protocols, transport protocols and payload optimization techniques and frameworks.
Experience Required:
4 years of relevant quantitative and qualitative experience in Research and Analytics as a graduate researcher. Industry experience is a plus.
Experience Preferred:
Education Required:
MS Engineering discipline in Computer Sciences, Electrical Engineering or any engineering discipline with relevant experience
Education Preferred:
PhD in Electrical Engineering, Computer Science or other related engineering disciplines
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May 24, 2019