AI Data Scientist – Autonomous Buildings

About Johnson Controls

At Johnson Controls, we transform the environments where people live, work, learn and play. From optimizing building performance to improving safety and enhancing comfort, we drive the outcomes that matter most. Dedicated to protecting the environment, we deliver our promise in industries such as healthcare, education, data centers and manufacturing. With a global team of 100,000 experts in more than 150 countries and over 130 years of innovation, we are the power behind our customers’ mission.

Johnson Controls OpenBlue is our blueprint for the future of smart buildings. It is a complete ecosystem of connected technologies, expertise, and services. Our products deliver analytics down to the space and system level to support property and facilities managers in optimizing their building operations. These tools empower our customers to improve energy efficiency, reduce carbon emissions, maximize tenant satisfaction, optimize asset performance, streamline maintenance operations, and enable healthy spaces that deliver comfort to all occupants.

What you will do

As an AI Data Scientist at Johnson Controls, you will help develop and maintain the AI algorithms and capabilities within our digital products. These applications will use data from commercial buildings apply machine learning or other advanced algorithms to provide value in the following ways:

• Automate and optimize building operation to reduce energy use
• Monitor and control indoor air quality to improve occupant wellness
• Generate actionable insights to improve facility manager productivity

Your efforts will ensure that our AI solutions deliver robust and repeatable outcomes through well-designed algorithms and well-written software.

To be successful in this role, the AI Data Scientist should be comfortable applying machine-learning concepts to practical applications while handling the inherent challenges of real-world datasets. We are looking especially for someone to help with autonomous building applications, including data-driven decision making and real-time optimization. Experience with HVAC and building energy systems will be especially valuable.

How you will do it

• Contribute as a member of the AI team with assigned tasks
• Collaborate with product managers to design new AI capabilities
• Explore and analyze available datasets for potential applications
• Write Python code to implement AI capabilities, especially closed-loop optimization
• Follow code-quality standards and best practices in software development
• Develop and maintain test cases to validate algorithm correctness
• Assess failures to identify causes and plan fixes for bugs
• Communicate key results to stakeholders
• Leverage JIRA to plan work and track issues

What we look for

Required

• Undergraduate degree in a relevant engineering field (mechanical, electrical, chemical, etc.) or computer science
• Four years of experience in applied data science or AI product development
• Proficiency in reading, writing, and troubleshooting Python code
• Competence in Python data-science packages (e.g., Numpy, Scipy, Pandas, Scikit-Learn, Keras, Tensorflow, Pytorch)
• Understanding of machine learning algorithms and techniques (e.g., regression, classification, clustering, and deep learning)
• Familiarity with optimal-control strategies (e.g., dynamic programming, model-predictive control, reinforcement learning)
• Excellent verbal and written communication skills

Nice to Have

• Graduate degree in a relevant engineering field (mechanical, electrical, chemical, etc.) or computer science
• Six years of experience in applied data science or AI product development

• Familiarity with HVAC systems and smart buildings
• Familiarity with thermodynamics and mass/energy balances
• Proficiency in optimal-control strategies (e.g., dynamic programming, model-predictive control, reinforcement learning)
• Familiarity with numerical optimization (e.g., linear/nonlinear programming, mixed-integer linear programming, metaheuristics)
• Familiarity with generative AI
• Familiarity with Python web frameworks and related tools (e.g., FastAPI, Pydantic)
• Experience with collaboration tools (e.g., Jira, Sharepoint, Teams)
• Experience with version control systems (e.g., Git, Github)