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.
What’s in it for you:
Be a part of our mission! 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. Do you dare to look at the world's challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what’s possible for a sustainable world.
Thrive at work and at home:
Benefits kick in on DAY ONE for you and your family, including health insurance and holistic wellness programs that include generous incentives – WE DARE TO CARE! Family building benefits include fertility coverage and adoption/surrogacy assistance. 401K match up to 6%, plus an additional 2% core contribution = up to 8% company contribution. Paid time off, including in support of volunteer and parental leave needs. Educational and training opportunities through company programs along with tuition assistance and student debt support. Learn more about our benefits here!Where is the work:
This position has been designated as a Hybrid work schedule with work performed onsite 3 days each week.
What you will do:
Thermo King is looking for a Senior Data Scientist to join a world-class team applying innovative analytic and data product approaches to complex problems. These analytics are leveraged by internal engineering, internal business functions, and our end customers to provide insights into product improvement and operational efficiency opportunities. This position is focused on advanced analytics and data products that combining statistical knowledge and programming capabilities to develop, test and maintain predictive machine learning models.
The role is responsible for leading and developing end to end analysis and data products, ranging from descriptive analysis to machine learning predictive algorithms. Work with product and business strategy teams to understand data product and visualization requirements. Communicate results to stakeholders, bridging analytics knowledge and engineering domain/business knowledge.Lead, develop, and document data-driven models and analytics for connected refrigeration and mobile HVAC systems. Analysis may include specific components and subsystems (e.g., compressors, heat exchangers, pumps, coils, fans--physical world analytics).Determine appropriate methods, prove viability of selected method, and educate internal teams as to the analytical foundation. Develop and maintain well documented analytics that are reproducible by othersCombine several sources of large-scale product data with both internal and external data sources to solve engineering and business analytic needs. Predictive failure analytics for units.Test and evaluate the quality of the algorithms using statistical methods.Develop and document data workflows to enable data extraction and merging of disparate data sets. Manage projects from start to finish, with implementation into a production environment as appropriate. Collaborate with engineers and other data scientists to solve problems and develop new products and services. Stay up to date in the field of machine learning. Apply new technologies in development of products. Responsibility for developing deliverables that are production capable (scalable, automation).What you will bring:
BS or MS in engineering, physics, computer science, data science, or statistics, with industrial internet of things data experience a plus. Looking for individuals with deep technical and data science expertise, acute strategic and analytical skills, ability to lead and persuade, drive and energy, and desire to work in a project-based environment on strategic issues.MS or BS with 4 years of experience applying data-driven modeling to solve technical problems.Familiarity with programming in R, Python, and/or SQL, or the ability to become proficient within a short period of time. Able to adapt to new technologies, as necessary. Familiarity with tools such as Alteryx, Tableau, etc. is a plus.Basic understanding of engineering data and physics-based models and simulations.Knowledge of machine learning modeling techniques, and experience visualizing model outputs for engineers, customers, and stakeholders. Experience in statistical inference, unsupervised machine learning, supervised machine learning, reliability/survivability models, and/or predictive maintenance.Good understanding of large-scale data mining and machine learning techniques for clustering, classification, regression, and anomaly detection.Knowledge of database systems including relational, column store and data marts; including understanding and documenting query development. Experience with Data engineering and Docker containers for automation a plusKnowledge or ability to become proficient quickly with version management tools such as Git or similar. 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.Compensation: $93,000-$180,000
Total compensation for this role will include a commission/incentive plan. Disclaimer: This base pay range is based on US national averages. Actual base pay could be a result of seniority, merit, geographic location where the work is performed.
Equal Employment Opportunity:
We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.