Innio LLC
Lead Data Scientist
Innio LLC, Waukesha, Wisconsin, United States, 53188
Description
Responsibilities:
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 partnersImplement complex algorithms and analytics from idea generation over development to product releaseApply advanced methods like machine and deep learning on a huge set of timeseries data combined with multiple data sources and typesWork on multiple projects simultaneously, supervise and guide Junior Data Scientists and InternsValidation of advanced models on INNIO's own developed IoT platform under consideration of lean and efficient codingUse 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 executionYour Qualifications:
Bachelor's or master's degree (or equivalent) in Computer Science, Mathematics or other related areas in engineeringWorking 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 analyticsExperience with machine learning techniquesStrong analytic and problem-solving skillsAffinity to design analytics on a high quality and maintainability levelNice to have:
Experience in additional programming languages (Java, JavaScript)Experience in consuming REST and GraphQL APIsExperience with cloud-based, containerized microservice architectures (Kubernetes, Docker)Engineering experience with internal combustion enginesEngineering experience in the gas compression or power generation applications
INNIO offers a great work environment, professional development, challenging careers, and competitive compensation. INNIO is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation, gender identity or expression, age, disability, veteran status or any other characteristics protected by law.
Responsibilities:
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 partnersImplement complex algorithms and analytics from idea generation over development to product releaseApply advanced methods like machine and deep learning on a huge set of timeseries data combined with multiple data sources and typesWork on multiple projects simultaneously, supervise and guide Junior Data Scientists and InternsValidation of advanced models on INNIO's own developed IoT platform under consideration of lean and efficient codingUse 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 executionYour Qualifications:
Bachelor's or master's degree (or equivalent) in Computer Science, Mathematics or other related areas in engineeringWorking 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 analyticsExperience with machine learning techniquesStrong analytic and problem-solving skillsAffinity to design analytics on a high quality and maintainability levelNice to have:
Experience in additional programming languages (Java, JavaScript)Experience in consuming REST and GraphQL APIsExperience with cloud-based, containerized microservice architectures (Kubernetes, Docker)Engineering experience with internal combustion enginesEngineering experience in the gas compression or power generation applications
INNIO offers a great work environment, professional development, challenging careers, and competitive compensation. INNIO is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation, gender identity or expression, age, disability, veteran status or any other characteristics protected by law.