Baltimore Aircoil Company | Data Engineer | Onsite | Baltimore, Maryland
At Baltimore Aircoil Company, our mission is to continually advance truly sustainable cooling – inspired by nature, powered by our people – for a world that depends on it to grow, succeed, and thrive.
Baltimore Aircoil Company is recognized as the world’s largest manufacturer of evaporative cooling, thermal storage, and heat transfer equipment. BAC products are sold to the commercial building market as components for air conditioning systems, to the food industry for air conditioning and refrigeration applications, and to a broad range of industries for process and power installations equipment cooling. The Data Engineer will sit at the headquarters in Jessup, MD. This facility houses the largest, most advanced R&amp;D laboratory complex of its kind, where innovations in evaporative cooling and heat transfer technology have originated in the past, are being developed today, and lead the industry into the future.
BAC’s Technology R&amp;D group discovers and develops game-changing technologies for the cooling industry. Successful technologies developed in this group become part of our core technologies and global product offerings. The Technology R&amp;D Data Engineer will be key for developing and implementing real-time data analysis and modeling technologies.
Principal Accountabilities
- Identify, analyze, and interpret trends or patterns in complex multivariate time series product performance data sets and develop custom models and algorithms
- Identify opportunities for technology, product, and system condition monitoring, control and optimization based on the available data sets and models developed
- Develop and deploy real-time product performance analytics tools and models in both internal and customer facing applications
- Create and deploy tools that support the extraction, transformation, loading and efficient analysis of data
- Define and implement new data collection, analysis, visualization, and storage processes
- Support a technical data-driven culture by enabling internal technical teams to expend available data analytics tools and models
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