Responsibilities:
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The Lead Data Scientist will work within the Waukesha engineering department with close contact to the Data Science Team of the INNIO Digital organization as well as strong collaboration with other cross-functional business functions (i.e. Research Partners, Controls Engineering, Service, Electrical Engineering and System Design, Mechanical Design, Thermodynamics, local IT departments)
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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
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Implement complex algorithms and analytics from idea generation over development to product release
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Apply advanced methods like machine and deep learning on a huge set of timeseries data combined with multiple data sources and types
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Work on multiple projects simultaneously, supervise and guide Junior Data Scientists and Interns
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Validation of advanced models on INNIO’s own developed IoT platform under consideration of lean and efficient coding
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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)
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Willingness to work independently and leverage available data, analyze, define path(s) to solution, and influence stakeholders in aligning to that path forward.
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Provide meaningful documentation for our service department and customers (user manuals, setup instructions, test reports and FAQ’s)
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Continuously communicate with stakeholders in technology/service engineering, service and operations departments to ensure efficient project execution
Minimum Qualifications:
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Bachelor’s or master's degree (or equivalent) in Computer Science, Mathematics or other related areas in Engineering
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Experience with machine learning techniques including applying them within a manufacturing, machining and/or related organizational environment.
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Proven ability to communicate & closely partner with a variety of cross-functional stakeholders and able to articulate the value proposition of data for use in making business decisions.
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Statistical and analytical algorithm design and technologies (Python, PyTorch, TensorFlow, SciKit)
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Software development and related processes including Agile Methodology (Scrum; Sprint; etc.)
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Demonstrated experience dealing with large time series data sets (Big Data)
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Experience in development of scalable algorithms or analytics
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Strong analytic and problem-solving skills
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Affinity to design analytics on a high quality and maintainability level
Preferred Qualifications:
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Engineering experience with internal combustion engines
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Engineering experience in the gas compression or power generation applications
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Experience in additional programming languages (Java, JavaScript)
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Experience in consuming REST and GraphQL APIs
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Experience with cloud-based, containerized microservice architectures (Kubernetes, Docker)
