Work in the Waukesha engineering department with close contact to the Data Science Team of the INNIO Digital organization as well as strong collaboration with other disciplines (i.e. Research Partners, Controls Engineering, Service, Electrical Engineering and System Design, Mechanical Design, Thermodynamics, local IT departments)
Develop new and existing Digital Waukesha products and manage the programs from an engineering point of view, working closely with our product line management team as well as partners
Implement complex algorithms and analytics from idea generation over development to product release
Apply advanced methods like machine and deep learning on a huge set of timeseries data combined with multiple data sources and types
Work on multiple projects simultaneously, supervise and guide Junior Data Scientists and Interns
Validation of advanced models on INNIO’s own developed IoT platform under consideration of lean and efficient coding
Use of modern software technologies for advanced analysis of sensor and engine data to find patterns and relationships to the condition of components and the engine (i.e. data mining, machine learning)
Willingness to work independently and leverage available data, analyze, define path(s) to solution, and influence stakeholders in aligning to that path forward.
Provide meaningful documentation for our service department and customers (user manuals, setup instructions, test reports and FAQ’s)
Continuously communicate with stakeholders in technology/service engineering, service and operations departments to ensure efficient project execution
Your Qualifications:
Bachelor’s or master's degree (or equivalent) in Computer Science, Mathematics or other related areas in engineering
Working experience in statistical and analytical algorithm design and technologies (Python, PyTorch, TensorFlow, SciKit)
Working experience in software development and related processes including Agile Methodology (Scrum; Sprint; etc.)
Familiarity in dealing with large time series data sets (Big Data)
Experience in development of scalable algorithms or analytics
Experience with machine learning techniques
Strong analytic and problem-solving skills
Affinity to design analytics on a high quality and maintainability level
Nice to have:
Experience in additional programming languages (Java, JavaScript)
Experience in consuming REST and GraphQL APIs
Experience with cloud-based, containerized microservice architectures (Kubernetes, Docker)
Engineering experience with internal combustion engines
Engineering experience in the gas compression or power generation applications
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