Senior Data Scientist
🔍 Minneapolis MN 314 W 90th St, Minneapolis, Minnesota, United States
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At Trane Technologies® we Challenge Possible. Our brands – including Trane® and Thermo King® - create access to cooling and comfort in buildings and homes, transport and protect food and perishables, connect customers to elevated performance with less environmental impact, dramatically reduce energy demands and carbon emissions, and innovate with a better world in mind. We boldly challenge what’s possible for a sustainable world.
We are open to any location in the US
Be a part of our mission! Do you want to directly contribute to an organization committed to reduce its customer carbon footprint by 1 Gigaton of Carbon Dioxide? As a world leader in creating comfortable, sustainable and efficient environments, it’s our responsibility to put the planet first. For us at Trane Technologies, sustainability is not just how we do business—it is our business. Sustainability is at the center of our strategy and influences how we make every decision.
Trane Technologies Modeling and Simulation NoE is seeking a Senior Data Scientist to join a world-class team applying innovative analytic approaches to extremely complex problems in the areas of industrial internet (IoT), equipment and building performance management and related engineering domains. The Senior Data Scientist Modeling and Simulation (M&S) designs, develops and implement state-of-the-art Artificial Intelligence (AI) and Machine Learning models applicable to Trane Technologies (TT) products as well as improves and standardizes application of tools and applications across different business units, providing sound guidance to end-users and sharing best practices globally. Establish external collaborations to build and leverage leading edge capabilities and techniques in this area of machine learning and data science. This position is focused on developing models to improve Trane technologies products, building energy modeling tools including modeling techniques, data richness and quality. The incumbent is also responsible for model management, integrating with existing systems, as well as identifying and implementing improvements to these processes.
Core Responsibilities:
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Development and implementation of state of the art statistical and machine learning models to enable predictive and prescriptive strategies
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Develop and improve performance models using machine learning for any instrumented piece of equipment and buildings, including specific components/subsystems (compressors, heat exchangers, pumps, coils and/or fans).
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Develop and enhance data driven models to support building models calibration, uncertainty and sensitivity analyses.
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Develop and implement forecasting and prediction strategies, to enhance the quality of physics based models.
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Provide recommendations and selection on the optimized data visualization capabilities, for a given data set
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Test and evaluate the quality of algorithms using statistical methods.
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Interface with engineers and modelers to create and improve understanding of predictive and descriptive models.
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Network across the organization to identify and communicate opportunities to apply data science and machine learning to product design and processes
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Mentor and guide other team members and colleagues in the domain area.
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Promote the use of data based modeling and simulation within the organization via value benefit analysis and similar demonstrations.
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Develop and maintain external collaborations to build and leverage cutting-edge capabilities. Participate and present in internal and external forums and conferences, related to data science and analytics.
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Document work per established internal standards and suggest improvements to procedures.
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Develop a clear understanding of customer requirements and meet or exceed those expectations.
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Conceptualize & develop project ideas leading to new advanced capability development in related domain areas to keep TT to the leading edge of technology.
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Lead internal tactical and strategic projects and reports project progress for quality, deliverables and cost.
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Potential future travel up to 5-10%
Qualifications:
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Master's Degree in Mathematics, Computer Science, Data Science or Statistics
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3+ years of experience applying data-driven modeling
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Demonstrated work or educational history in engineering and/or engineering related disciplines, including but not limited to differential equations, heat transfer, electrical engineering, controls, HVAC, IoT or embedded technologies highly preferred
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Leadership experience is a plus
Key Competencies:
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Intermediate knowledge in at least two of the following technologies: R, Python, SQL, MATLAB and ability to adapt to new technologies, as necessary. Familiarity with tools such as Alteryx, SAS, Tableau, RapidMiner is a plus.
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Understanding of engineering data and physics-based models and simulations.
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Sufficient knowledge of machine learning modeling techniques, and experience visualizing model outputs for engineers, customers and stakeholders.
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Communicate compellingly. Convert insights from analytics to stories. Be an advocate for data science and machine learning, and how to create new capabilities and drive transformation.
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Experience in statistical inference, unsupervised machine learning, supervised machine learning, reliability/survivability models, and/or predictive maintenance. Basic experience with neural nets, cross validation, hyperparameter tuning is desired.
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Good understanding of large-scale data mining and machine learning techniques for clustering, classification, regression, and anomaly detection.
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Ability to manipulate and visualize both structured and non-structured datasets.
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Advanced knowledge of database systems including relational, column store and data marts
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Strong written & verbal English communication skills to interface effectively with team members, customers and stakeholders (senior leaders) in North America and other parts of the world.
We offer competitive compensation and comprehensive benefits and programs that help our employees thrive in both their professional and personal lives. We are proud of our winning culture which is inclusive and respectful at its core. We share passion for serving customers, caring for others, and boldly challenging what’s possible for a sustainable world.
We are committed to achieving workforce diversity reflective of our communities. We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identify, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.
We are committed to achieving workforce diversity reflective of our communities. We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identify, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.